Used Chevrolet Corvette Stingray Z51 2015 For Sale In Apopka FL - 109214\n2015 Chevrolet Corvette Stingray Z51 RWD Apopka FL\nStock #: 109214\nExt Color: Laguna Blue Tintcoat\n**19in WHEELS**, **LOCAL ORLANDO AREA TRADE**, **LEATHER SEATING**, Painted Body-Color Carbon Fiber Removable Roof Panel, Premium audio system: Chevrolet MyLink, Steering wheel mounted audio controls. 6.2L V8 Priced below KBB Fair Purchase Price!\n2007 Chevrolet Corvette Z06 RWD\n2015 Chevrolet Corvette Stingray Z51 RWD\nI would like to confirm the availability of this 2015 Chevrolet Corvette Stingray Z51 RWD - 109214\nI would like to request more information on this 2015 Chevrolet Corvette Stingray Z51 RWD - 109214\nI would to reserve this vehicle today: 2015 Chevrolet Corvette Stingray Z51 RWD - 109214\nCheck out this 2015 Chevrolet Corvette Stingray Z51 RWD


2022-06-27 Impact of Acoustic Event Tagging on Scene Classification in a Multi-Task Learning Framework Rahil Parikh, Harshavardhan Sundar, Ming Sun, Chao Wang, Spyros Matsoukas arXiv_AI arXiv_AI Scene_Classification Regularization Classification PDF\n2022-06-16 DCASE 2022: Comparative Analysis Of CNNs For Acoustic Scene Classification Under Low-Complexity Considerations Josep Zaragoza-Paredes, Javier Naranjo-Alcazar, Valery Naranjo, Pedro Zuccarello arXiv_SD arXiv_SD Scene_Classification Classification Inference Prediction Matching PDF\n2022-06-13 Low-complexity deep learning frameworks for acoustic scene classification Lam Pham, Dat Ngo, Anahid Jalali, Alexander Schindler arXiv_SD arXiv_SD Scene_Classification Pose Action Classification Deep_Learning PDF\n2022-06-02 Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment Shanshan Wang, Archontis Politis, Annamaria Mesaros, Tuomas Virtanen arXiv_SD arXiv_SD Recognition Scene_Classification Represenation_Learning Self-Supervised Pose Action_Recognition Action Classification Detection Object_Detection PDF\n2022-05-27 Learning Instance Representation Banks for Aerial Scene Classification Jingjun Yi, Beichen Zhou arXiv_CV arXiv_CV Scene_Classification Pose Classification GAN PDF\n2022-05-17 Pairwise Comparison Network for Remote Sensing Scene Classification Zhang Yue, Zheng Xiangtao, Lu Xiaoqiang arXiv_AI arXiv_AI Scene_Classification Pose Classification CNN PDF\n2022-05-06 All Grains, One Scheme : Learning Multi-grain Instance Representation for Aerial Scene Classification Qi Bi, Beichen Zhou, Kun Qin, Qinghao Ye, Gui-Song Xia arXiv_CV arXiv_CV Scene_Classification Knowledge Pose Classification CNN PDF\n2022-05-01 Relation-guided acoustic scene classification aided with event embeddings Yuanbo Hou, Bo Kang, Wout Van Hauwermeiren, Dick Botteldooren arXiv_SD arXiv_SD Embedding Recognition Scene_Classification Pose Classification Relation PDF\n2022-04-26 A Comparative Study on Approaches to Acoustic Scene Classification using CNNs Ishrat Jahan Ananya, Sarah Suad, Shadab Hafiz Choudhury, Mohammad Ashrafuzzaman Khan arXiv_AI arXiv_AI Embedding Scene_Classification Classification PDF\n2022-04-25 Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy Chengxin Chen, Meng Wang, Pengyuan Zhang arXiv_CV arXiv_CV Embedding Transfer_Learning Scene_Classification Optimization Pose Classification Attention PDF\n2022-04-10 TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning Chao Tao, Ji Qia, Guo Zhang, Qing Zhu, Weipeng Lu, Haifeng Li arXiv_AI arXiv_AI Image_Caption Segmentation Semantic_Segmentation Scene_Classification Optimization Knowledge Self-Supervised Pose Classification Detection Object_Detection PDF\n2022-04-05 How Information on Acoustic Scenes and Sound Events Mutually Benefits Event Detection and Scene Classification Tasks Keisuke Imoto, Yuka Komatsu, Shunsuke Tsubaki, Tatsuya Komatsu arXiv_SD arXiv_SD Scene_Classification Adversarial Pose Classification Deep_Learning Detection PDF\n2022-03-31 1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality Arshdeep Singh arXiv_SD arXiv_SD Embedding Scene_Classification Pose Classification CNN PDF\n2022-03-29 A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification Arshdeep Singh, Mark D. Plumbley arXiv_AI arXiv_AI Scene_Classification Pose Classification CNN Inference PDF\n2022-03-29 A Multi-Stage Duplex Fusion ConvNet for Aerial Scene Classification Jingjun Yi, Beichen Zhou arXiv_AI arXiv_AI Scene_Classification Classification Deep_Learning Drone CNN PDF\n2022-03-23 Wider or Deeper Neural Network Architecture for Acoustic Scene Classification with Mismatched Recording Devices Lam Pham, Khoa Dinh, Dat Ngo, Hieu Tang, Alexander Schindler arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2022-03-16 Instance-level loss based multiple-instance learning for acoustic scene classification Won-Gook Choi, Joon-Hyuk Chang, Jae-Mo Yang, Han-Gil Moon arXiv_SD arXiv_SD Scene_Classification Weakly_Supervised Pose Classification CNN PDF\n2022-03-16 A Squeeze-and-Excitation and Transformer based Cross-task System for Environmental Sound Recognition Jisheng Bai, Jianfeng Chen, Mou Wang, Muhammad Saad Ayub arXiv_SD arXiv_SD Transformer Recognition Scene_Classification Knowledge Pose Classification Detection Relation Attention PDF\n2022-03-07 Deep Neural Decision Forest for Acoustic Scene Classification Jianyuan Sun, Xubo Liu, Xinhao Mei, Jinzheng Zhao, Mark D. Plumbley, Volkan Kılıç, Wenwu Wang arXiv_AI arXiv_AI Scene_Classification Pose Classification Deep_Learning Attention CNN PDF\n2022-03-07 A study on joint modeling and data augmentation of multi-modalities for audio-visual scene classification Qing Wang, Jun Du, Siyuan Zheng, Yunqing Li, Yajian Wang, Yuzhong Wu, Hu Hu, Chao-Han Huck Yang, Sabato Marco Siniscalchi, Yannan Wang, Chin-Hui Lee arXiv_SD arXiv_SD Embedding Scene_Classification Pose Classification PDF\n2022-03-04 Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification Qiaoling Chen, Zhihao Chen, Wei Luo arXiv_CV arXiv_CV Scene_Classification Pose Classification Few-Shot PDF\n2022-02-15 Debiased Pseudo Labeling in Self-Training Baixu Chen, Junguang Jiang, Ximei Wang, Jianmin Wang, Mingsheng Long arXiv_CV arXiv_CV Recognition Scene_Classification Pose Classification PDF\n2022-02-14 Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark Yonghao Xu, Pedram Ghamisi arXiv_CV arXiv_CV Segmentation Semantic_Segmentation Scene_Classification Knowledge Adversarial Pose Classification PDF\n2021-12-26 Acoustic scene classification using auditory datasets Jayesh Kumpawat, Shubhajit Dey arXiv_SD arXiv_SD Scene_Classification Classification Deep_Learning PDF\n2021-12-21 Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systems Xu Kang, Bin Song, Jie Guo, Zhijin Qin, F. Richard Yu arXiv_CV arXiv_CV Reinforcement_Learning Scene_Classification Pose Classification Deep_Learning PDF\n2021-12-16 An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification Lam Pham, Dat Ngo, Phu X. Nguyen, Truong Hoang, Alexander Schindler arXiv_CV arXiv_CV Scene_Classification Pose Classification Deep_Learning PDF\n2021-12-09 On The Effect Of Coding Artifacts On Acoustic Scene Classification Nagashree K. S. Rao, Nils Peters arXiv_SD arXiv_SD Scene_Classification Classification PDF\n2021-12-07 RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition Cheng Peng, Yangyang Li, Ronghua Shang, Licheng Jiao arXiv_AI arXiv_AI NAS Recognition Scene_Classification Knowledge Pose Classification Deep_Learning Detection Object_Detection PDF\n2021-11-21 Health Monitoring of Industrial machines using Scene-Aware Threshold Selection Arshdeep Singh, Raju Arvind, Padmanabhan Rajan arXiv_AI arXiv_AI Reconstruction Unsupervised Scene_Classification Pose Classification PDF\n2021-11-12 Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization Byeonggeun Kim, Seunghan Yang, Jangho Kim, Simyung Chang arXiv_SD arXiv_SD Quantization Scene_Classification Knowledge Pose Classification PDF\n2021-11-05 The Role of Pre-Training in High-Resolution Remote Sensing Scene Classification Vladimir Risojević, Vladan Stojnić arXiv_CV arXiv_CV Scene_Classification Classification PDF\n2021-11-05 Remote Sensing Image Super-resolution and Object Detection: Benchmark and State of the Art Yi Wang, Syed Muhammad Arsalan Bashir, Mahrukh Khan, Qudrat Ullah, Rui Wang, Yilin Song, Zhe Guo, Yilong Niu arXiv_AI arXiv_AI Super_Resolution Scene_Classification Review Adversarial Pose Classification Deep_Learning Detection Object_Detection PDF\n2021-10-27 SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation Abhinav Moudgil, Arjun Majumdar, Harsh Agrawal, Stefan Lee, Dhruv Batra arXiv_CV arXiv_CV Transformer Scene_Classification Classification Detection Object_Detection PDF\n2021-10-26 Towards Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning Jakob Abeßer, Meinard Müller arXiv_SD arXiv_SD Embedding Unsupervised Scene_Classification Pose Classification PDF\n2021-10-18 Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording Devices Stanisław Kacprzak, Konrad Kowalczyk arXiv_SD arXiv_SD Scene_Classification Adversarial Classification GAN PDF\n2021-10-16 A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge Transfer Hu Hu, Sabato Marco Siniscalchi, Chao-Han Huck Yang, Chin-Hui Lee arXiv_AI arXiv_AI Scene_Classification Knowledge Pose Classification Attention Inference PDF\n2021-10-14 ASK: Adaptively Selecting Key Local Features for RGB-D Scene Recognition Zhitong Xiong, Yuan Yuan, Qi Wang arXiv_CV arXiv_CV Recognition Scene_Classification Pose Classification Relation PDF\n2021-10-09 Visually Exploring Multi-Purpose Audio Data David Heise, Helen L. Bear arXiv_SD arXiv_SD Unsupervised Scene_Classification Self-Supervised Pose Classification PDF\n2021-10-09 SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification Baoquan Zhang, Shanshan Feng, Xutao Li, Yunming Ye, Rui Ye arXiv_CV arXiv_CV Scene_Classification Pose Classification Relation Few-Shot Image_Classification Prediction Matching PDF\n2021-09-25 An embarrassingly simple comparison of machine learning algorithms for indoor scene classification Bhanuka Manesha Samarasekara Vitharana Gamage arXiv_CV arXiv_CV NAS Recognition Scene_Classification Pose Classification Autonomous PDF\n2021-08-13 Cross-modal Spectrum Transformation Network For Acoustic Scene classification Yang Liu, Alexandros Neophytou, Sunando Sengupta, Eric Sommerlade arXiv_SD arXiv_SD Scene_Classification Pose Classification Relation CNN PDF\n2021-08-11 Robust Feature Learning on Long-Duration Sounds for Acoustic Scene Classification Yuzhong Wu, Tan Lee arXiv_AI arXiv_AI Scene_Classification Pose Classification CNN PDF\n2021-08-06 SpecMix : A Mixed Sample Data Augmentation method for Training withTime-Frequency Domain Features Gwantae Kim, David K. Han, Hanseok Ko arXiv_SD arXiv_SD Enhancement Scene_Classification Speech Pose Classification Relation Image_Classification PDF\n2021-08-02 Robust Acoustic Scene Classification in the Presence of Active Foreground Speech Siyuan Song, Brecht Desplanques, Celest De Moor, Kris Demuynck, Nilesh Madhu arXiv_SD arXiv_SD Scene_Classification Speech Pose Classification PDF\n2021-07-30 Task 1A DCASE 2021: Acoustic Scene Classification with mismatch-devices using squeeze-excitation technique and low-complexity constraint Javier Naranjo-Alcazar, Sergi Perez-Castanos, Maximo Cobos, Francesc J. Ferri, Pedro Zuccarello arXiv_SD arXiv_SD Scene_Classification Pose Classification CNN PDF\n2021-07-30 Enhancing Social Relation Inference with Concise Interaction Graph and Discriminative Scene Representation Xiaotian Yu, Hanling Yi, Yi Yu, Ling Xing, Shiliang Zhang, Xiaoyu Wang arXiv_AI arXiv_AI Scene_Classification Pose Contrastive_Learning Action Classification Relation CNN Inference PDF\n2021-07-28 Squeeze-Excitation Convolutional Recurrent Neural Networks for Audio-Visual Scene Classification Javier Naranjo-Alcazar, Sergi Perez-Castanos, Aaron Lopez-Garcia, Pedro Zuccarello, Maximo Cobos, Francesc J. Ferri arXiv_SD arXiv_SD Scene_Classification RNN Pose Classification CNN Prediction PDF\n2021-07-20 Robust Deep Learning Frameworks for Acoustic Scene and Respiratory Sound Classification Lam Pham arXiv_SD arXiv_SD Embedding Scene_Classification Pose Action Classification Deep_Learning Medical PDF\n2021-07-19 Over-Parameterization and Generalization in Audio Classification Khaled Koutini, Hamid Eghbal-zadeh, Florian Henkel, Jan Schlüter, Gerhard Widmer arXiv_SD arXiv_SD Scene_Classification Classification Relation CNN PDF\n2021-07-12 Geographical Knowledge-driven Representation Learning for Remote Sensing Images Wenyuan Li, Keyan Chen, Hao Chen, Zhenwei Shi arXiv_CV arXiv_CV Segmentation Semantic_Segmentation Scene_Classification Represenation_Learning Knowledge Self-Supervised Pose Classification Deep_Learning Detection Object_Detection PDF\n2021-07-03 A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification Chao-Han Huck Yang, Hu Hu, Sabato Marco Siniscalchi, Qing Wang, Yuyang Wang, Xianjun Xia, Yuanjun Zhao, Yuzhong Wu, Yannan Wang, Jun Du, Chin-Hui Lee arXiv_SD arXiv_SD Quantization Scene_Classification Knowledge Pose Classification PDF\n2021-06-18 A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention Muhammad Monjurul Karim, Yu Li, Ruwen Qin, Zhaozheng Yin arXiv_AI arXiv_AI Scene_Classification Pose Classification Deep_Learning Autonomous PDF\n2021-06-15 A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification Md Adnan Arefeen, Sumaiya Tabassum Nimi, Md Yusuf Sarwar Uddin, Zhu Li arXiv_CV arXiv_CV Scene_Classification Pose Classification Image_Classification PDF\n2021-06-12 Deep Learning Frameworks Applied For Audio-Visual Scene Classification Lam Pham, Alexander Schindler, Mina Schütz, Jasmin Lampert, Sven Schlarb, Ross King arXiv_SD arXiv_SD Scene_Classification Classification Deep_Learning Detection PDF\n2021-06-12 A Low-Compexity Deep Learning Framework For Acoustic Scene Classification Lam Pham, Hieu Tang, Anahid Jalali, Alexander Schindler, Ross King arXiv_SD arXiv_SD Scene_Classification Pose Action Classification Deep_Learning Detection CNN PDF\n2021-05-28 Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions Shanshan Wang, Toni Heittola, Annamaria Mesaros, Tuomas Virtanen arXiv_SD arXiv_SD Scene_Classification Classification PDF\n2021-05-26 Receptive Field Regularization Techniques for Audio Classification and Tagging with Deep Convolutional Neural Networks Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer arXiv_SD arXiv_SD Recognition Scene_Classification Regularization Pose Emotion Classification Detection CNN PDF\n2021-05-25 Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices Michał Kośmider arXiv_SD arXiv_SD Scene_Classification Pose Action Classification Detection Relation PDF\n2021-05-21 Unsupervised Multi-Target Domain Adaptation for Acoustic Scene Classification Dongchao Yang, Helin Wang, Yuexian Zou arXiv_SD arXiv_SD Unsupervised Scene_Classification Adversarial Pose Face Classification Relation Attention PDF\n2021-05-17 Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report Andrey Ignatov, Grigory Malivenko, Radu Timofte, Sheng Chen, Xin Xia, Zhaoyan Liu, Yuwei Zhang, Feng Zhu, Jiashi Li, Xuefeng Xiao, Yuan Tian, Xinglong Wu, Christos Kyrkou, Yixin Chen, Zexin Zhang, Yunbo Peng, Yue Lin, Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah, Himanshu Kumar, Chao Ge, Pei-Lin Wu, Jin-Hua Du, Andrew Batutin, Juan Pablo Federico, Konrad Lyda, Levon Khojoyan, Abhishek Thanki, Sayak Paul, Shahid Siddiqui arXiv_CV arXiv_CV Scene_Classification Pose Classification Deep_Learning Detection PDF\n2021-05-05 Acoustic Scene Classification Using Multichannel Observation with Partially Missing Channels Keisuke Imoto arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2021-04-22 Mini-batch graphs for robust image classification Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi arXiv_AI arXiv_AI Scene_Classification Adversarial Classification Deep_Learning Relation GAN Image_Classification PDF\n2021-04-15 Attentive Max Feature Map for Acoustic Scene Classification with Joint Learning considering the Abstraction of Classes Hye-jin Shim, Ju-ho Kim, Jee-weon Jung, Ha-Jin Yu arXiv_AI arXiv_AI Scene_Classification Pose Action Classification Attention PDF\n2021-04-01 Remote Sensing Image Classification with the SEN12MS Dataset Michael Schmitt, Yu-Lun Wu arXiv_CV arXiv_CV Scene_Classification Classification Deep_Learning CNN Image_Classification PDF\n2021-04-01 Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification Qi Zhao, Yujing Ma, Shuchang Lyu, Lijiang Chen arXiv_CV arXiv_CV Scene_Classification Knowledge Pose Face Classification Inference PDF\n2021-03-31 SpecAugment++: A Hidden Space Data Augmentation Method for Acoustic Scene Classification Helin Wang, Yuexian Zou, Wenwu Wang arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2021-03-30 Environmental sound analysis with mixup based multitask learning and cross-task fusion Weiping Zheng, Dacan Jiang, Gansen Zhao arXiv_CV arXiv_CV Scene_Classification Pose Classification Attention CNN PDF\n2021-03-29 A Hierarchical Approach to Remote Sensing Scene Classification Ozlem Sen, Hacer Yalim Keles arXiv_CV arXiv_CV Scene_Classification Classification PDF\n2021-03-26 Translate to Adapt: RGB-D Scene Recognition across Domains Andrea Ferreri, Silvia Bucci, Tatiana Tommasi arXiv_CV arXiv_CV Recognition Scene_Classification 3D Self-Supervised Pose Classification PDF\n2021-03-18 MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels Pablo Gómez, Gabriele Meoni arXiv_CV arXiv_CV Scene_Classification Knowledge Classification Deep_Learning PDF\n2021-02-25 Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech Juliette Millet, Jean-Remi King arXiv_CL arXiv_CL Scene_Classification Speech Classification Deep_Learning PDF\n2021-02-23 Investigating Local and Global Information for Automated Audio Captioning with Transfer Learning Xuenan Xu, Heinrich Dinkel, Mengyue Wu, Zeyu Xie, Kai Yu arXiv_SD arXiv_SD Transfer_Learning Scene_Classification Represenation_Learning Pose Classification Relation Caption PDF\n2021-01-26 Deep Learning for Scene Classification: A Survey Delu Zeng (1), Minyu Liao (1), Mohammad Tavakolian (2), Yulan Guo (3, 4), Bolei Zhou (5), Dewen Hu (3), Matti Pietikäinen (2), Li Liu (2, 3) ((1) South China University of Technology, (2) University of Oulu, (3) National University of Defense Technology, (4) Sun Yatsen University, (5) Chinese University of Hong Kong) arXiv_CV arXiv_CV Scene_Classification Review Survey Quantitative Classification Deep_Learning PDF\n2021-01-25 HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks Yunxiang Zhao, Qiuhong Ke, Flip Korn, Jianzhong Qi, Rui Zhang arXiv_CV arXiv_CV Scene_Classification Classification CNN PDF\n2020-12-29 MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification Qi Zhao, Shuchang Lyu, Yuewen Li, Yujing Ma, Lijiang Chen arXiv_AI arXiv_AI Scene_Classification Pose Classification Prediction PDF\n2020-11-18 CAA-Net: Conditional Atrous CNNs with Attention for Explainable Device-robust Acoustic Scene Classification Zhao Ren, Qiuqiang Kong, Jing Han, Mark D. Plumbley, Björn W. Schuller arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection Attention CNN PDF\n2020-11-05 Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping Khaled Koutini, Florian Henkel, Hamid Eghbal-zadeh, Gerhard Widmer arXiv_SD arXiv_SD Scene_Classification Regularization Pose Classification PDF\n2020-11-03 A Two-Stage Approach to Device-Robust Acoustic Scene Classification Hu Hu, Chao-Han Huck Yang, Xianjun Xia, Xue Bai, Xin Tang, Yajian Wang, Shutong Niu, Li Chai, Juanjuan Li, Hongning Zhu, Feng Bao, Yuanjun Zhao, Sabato Marco Siniscalchi, Yannan Wang, Jun Du, Chin-Hui Lee arXiv_SD arXiv_SD Scene_Classification Salient Pose Classification CNN PDF\n2020-10-18 Exploiting Context for Robustness to Label Noise in Active Learning Sudipta Paul, Shivkumar Chandrasekaran, B.S. Manjunath, Amit K. Roy-Chowdhury arXiv_CV arXiv_CV Recognition Scene_Classification Pose Classification Relation Activity PDF\n2020-10-16 What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions Kiana Ehsani, Daniel Gordon, Thomas Nguyen, Roozbeh Mottaghi, Ali Farhadi arXiv_CV arXiv_CV Recognition Scene_Classification Represenation_Learning Self-Supervised Face Action_Recognition Action Classification Attention Prediction PDF\n2020-10-16 Joint Analysis of Sound Events and Acoustic Scenes Using Multitask Learning Noriyuki Tonami, Keisuke Imoto, Ryosuke Yamanishi, Yoichi Yamashita arXiv_SD arXiv_SD Scene_Classification RNN Pose Classification Detection CNN PDF\n2020-10-02 Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples Chao Tao, Ji Qi, Weipeng Lu, Hao Wang, Haifeng Li arXiv_CV arXiv_CV Scene_Classification Self-Supervised Classification Deep_Learning PDF\n2020-09-29 A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification Hichame Yessou, Gencer Sumbul, Begüm Demir arXiv_CV arXiv_CV Scene_Classification Sparse Classification Deep_Learning Image_Classification PDF\n2020-09-28 RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification Haifeng Li, Zhenqi Cui, Zhiqing Zhu, Li Chen, Jiawei Zhu, Haozhe Huang, Chao Tao arXiv_CV arXiv_CV Segmentation Scene_Classification Pose Face Classification Few-Shot GAN PDF\n2020-09-23 2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification Albert Mosella-Montoro, Javier Ruiz-Hidalgo arXiv_AI arXiv_AI Embedding Scene_Classification 3D Pose Classification CNN PDF\n2020-09-20 Deriving Visual Semantics from Spatial Context: An Adaptation of LSA and Word2Vec to generate Object and Scene Embeddings from Images Matthias S. Treder, Juan Mayor-Torres, Christoph Teufel arXiv_CV arXiv_CV Embedding Scene_Classification Classification Language_Model PDF\n2020-09-16 DAER to Reject Seeds with Dual-loss Additional Error Regression Stephan J. Lemmer, Jason J. Corso arXiv_CV arXiv_CV Segmentation Scene_Classification Review Pose Classification Inference PDF\n2020-09-10 Understanding the Role of Individual Units in a Deep Neural Network David Bau, Jun-Yan Zhu, Hendrik Strobelt, Agata Lapedriza, Bolei Zhou, Antonio Torralba arXiv_CV arXiv_CV Scene_Classification Adversarial Classification GAN CNN Image_Classification PDF\n2020-08-31 Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle Decisions Shih-Yuan Yu, Arnav V. Malawade, Deepan Muthirayan, Pramod P. Khargonekar, Mohammad A. Al Faruque arXiv_CV arXiv_CV Scene_Classification Knowledge Pose Face Classification Deep_Learning Relation Attention Autonomous PDF\n2020-08-17 Deep Learning Based Open Set Acoustic Scene Classification Zuzanna Kwiatkowska, Beniamin Kalinowski, Michał Kośmider, Krzysztof Rykaczewski arXiv_SD arXiv_SD Scene_Classification Knowledge Classification Deep_Learning Detection Inference PDF\n2020-08-05 Neural Architecture Search on Acoustic Scene Classification Jixiang Li, Chuming Liang, Bo Zhang, Zhao Wang, Fei Xiang, Xiangxiang Chu arXiv_SD arXiv_SD NAS Scene_Classification Pose Classification CNN PDF\n2020-08-03 AiRound and CV-BrCT: Novel Multi-View Datasets for Scene Classification Gabriel Machado, Edemir Ferreira, Keiller Nogueira, Hugo Oliveira, Pedro Gama, Jefersson A. dos Santos arXiv_CV arXiv_CV Scene_Classification Pose Classification Image_Classification PDF\n2020-07-31 Relational Teacher Student Learning with Neural Label Embedding for Device Adaptation in Acoustic Scene Classification Hu Hu, Sabato Marco Siniscalchi, Yannan Wang, Chin-Hui Lee arXiv_CL arXiv_CL Embedding Scene_Classification Knowledge Pose Classification Relation PDF\n2020-07-31 An Acoustic Segment Model Based Segment Unit Selection Approach to Acoustic Scene Classification with Partial Utterances Hu Hu, Sabato Marco Siniscalchi, Yannan Wang, Xue Bai, Jun Du, Chin-Hui Lee arXiv_CL arXiv_CL Scene_Classification Pose Classification Attention PDF\n2020-07-25 DD-CNN: Depthwise Disout Convolutional Neural Network for Low-complexity Acoustic Scene Classification Jingqiao Zhao, Zhen-Hua Feng, Qiuqiang Kong, Xiaoning Song, Xiao-Jun Wu arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection CNN PDF\n2020-07-16 Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation Hu Hu, Chao-Han Huck Yang, Xianjun Xia, Xue Bai, Xin Tang, Yajian Wang, Shutong Niu, Li Chai, Juanjuan Li, Hongning Zhu, Feng Bao, Yuanjun Zhao, Sabato Marco Siniscalchi, Yannan Wang, Jun Du, Chin-Hui Lee arXiv_SD arXiv_SD Quantization Scene_Classification Pose Classification CNN PDF\n2020-07-11 Look and Listen: A Multi-modality Late Fusion Approach to Scene Classification for Autonomous Machines Jordan J. Bird, Diego R. Faria, Cristiano Premebida, Anikó Ekárt, George Vogiatzis arXiv_AI arXiv_AI Scene_Classification Classification Autonomous PDF\n2020-07-09 Capturing scattered discriminative information using a deep architecture in acoustic scene classification Hye-jin Shim, Jee-weon Jung, Ju-ho Kim, Ha-jin Yu arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection PDF\n2020-07-09 PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, Mark D. Plumbley arXiv_SD arXiv_SD Recognition Scene_Classification Speech Pose Emotion Classification Detection CNN PDF\n2020-07-08 Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision Abhinav Shukla, Stavros Petridis, Maja Pantic arXiv_CV arXiv_CV Recognition Scene_Classification Speech Self-Supervised Pose Face Action_Recognition Action Classification PDF\n2020-07-06 Acoustic Scene Classification with Spectrogram Processing Strategies Helin Wang, Yuexian Zou, Dading Chong arXiv_SD arXiv_SD Scene_Classification Pose Classification CNN PDF\n2020-07-02 Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture Jinhua Liang, Tao Zhang, Guoqing Feng arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection Attention CNN Image_Classification PDF\n2020-07-01 A Transformer-based Audio Captioning Model with Keyword Estimation Yuma Koizumi, Ryo Masumura, Kyosuke Nishida, Masahiro Yasuda, Shoichiro Saito arXiv_SD arXiv_SD Transformer Scene_Classification Pose Classification Detection Caption PDF\n2020-06-22 DiRS: On Creating Benchmark Datasets for Remote Sensing Image Interpretation Yang Long, Gui-Song Xia, Shengyang Li, Wen Yang, Michael Ying Yang, Xiao Xiang Zhu, Liangpei Zhang, Deren Li arXiv_CV arXiv_CV Scene_Classification Review Classification Image_Classification PDF\n2020-06-20 Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain Akshara Preethy Byju, Gencer Sumbul, Begüm Demir, Lorenzo Bruzzone arXiv_CV arXiv_CV Scene_Classification Pose Classification CNN PDF\n2020-06-03 Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion Lixiang Ru, Bo Du, Chen Wu arXiv_CV arXiv_CV Embedding Scene_Classification Pose Classification Detection Relation CNN PDF\n2020-05-27 ACGAN-based Data Augmentation Integrated with Long-term Scalogram for Acoustic Scene Classification Hangting Chen, Zuozhen Liu, Zongming Liu, Pengyuan Zhang arXiv_SD arXiv_SD Scene_Classification Adversarial Pose Action Classification Detection GAN PDF\n2020-05-26 Sound Context Classification Basing on Join Learning Model and Multi-Spectrogram Features Dat Ngo, Hao Hoang, Anh Nguyen, Tien Ly, Lam Pham arXiv_SD arXiv_SD Scene_Classification Text_Classification Pose Action Classification Deep_Learning Detection CNN PDF\n2020-05-03 Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities Gong Cheng, Xingxing Xie, Junwei Han, Lei Guo, Gui-Song Xia arXiv_CV arXiv_CV Scene_Classification Knowledge Review Adversarial Survey Classification Deep_Learning Attention CNN PDF\n2020-04-30 Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching Alessandro Ilic Mezza, Emanuël A. P. Habets, Meinard Müller, Augusto Sarti arXiv_SD arXiv_SD Unsupervised Scene_Classification Pose Classification Matching PDF\n2020-04-09 Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification S. Wang, Y. Guan, L. Shao arXiv_CV arXiv_CV Scene_Classification Pose Classification PDF\n2020-03-20 On the performance of different excitation-residual blocks for Acoustic Scene Classification Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarello, Maximo Cobos arXiv_SD arXiv_SD Scene_Classification Pose Classification Relation GAN CNN PDF\n2020-03-02 DEEVA: A Deep Learning and IoT Based Computer Vision System to Address Safety and Security of Production Sites in Energy Industry Nimish M. Awalgaonkar, Haining Zheng, Christopher S. Gurciullo arXiv_CV arXiv_CV Surveillance Segmentation Transfer_Learning Semantic_Segmentation Recognition Scene_Classification Knowledge Action Classification Deep_Learning Detection Object_Detection Caption PDF\n2020-02-22 Multi-Representation Knowledge Distillation For Audio Classification Liang Gao, Kele Xu, Huaimin Wang, Yuxing Peng arXiv_SD arXiv_SD Scene_Classification Knowledge Pose Classification Attention Inference PDF\n2020-02-14 Acoustic Scene Classification Using Bilinear Pooling on Time-liked and Frequency-liked Convolution Neural Network Xing Yong Kek, Cheng Siong Chin, Ye Li arXiv_SD arXiv_SD Scene_Classification Classification CNN PDF\n2020-02-14 Sound Event Detection by Multitask Learning of Sound Events and Scenes with Soft Scene Labels Keisuke Imoto, Noriyuki Tonami, Yuma Koizumi, Masahiro Yasuda, Ryosuke Yamanishi, Yoichi Yamashita arXiv_SD arXiv_SD Scene_Classification Knowledge Pose Classification Detection Relation PDF\n2020-02-12 Deep Feature Embedding and Hierarchical Classification for Audio Scene Classification Lam Pham, Ian McLoughlin, Huy Phan, Ramaswamy Palaniappan, Alfred Mertins arXiv_SD arXiv_SD Embedding Scene_Classification Pose Classification CNN PDF\n2020-02-11 Robust Acoustic Scene Classification using a Multi-Spectrogram Encoder-Decoder Framework Lam Pham, Huy Phan, Truc Nguyen, Ramaswamy Palaniappan, Alfred Mertins, Ian McLoughlin arXiv_SD arXiv_SD Scene_Classification Pose Action Classification Detection PDF\n2020-02-11 Vision-based Fight Detection from Surveillance Cameras Şeymanur Aktı, Gözde Ayşe Tataroğlu, Hazım Kemal Ekenel arXiv_AI arXiv_AI Surveillance Recognition Scene_Classification RNN Pose Action_Recognition Action Classification Detection Attention PDF\n2020-01-27 Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification Jie Chen, Haozhe Huang, Jian Peng, Jiawei Zhu, Li Chen, Wenbo Li, Binyu Sun, Haifeng Li arXiv_CV arXiv_CV Gradient_Descent Scene_Classification Knowledge Pose Classification Deep_Learning CNN PDF\n2019-11-28 A Discriminative Learned CNN Embedding For Remote Senseing Image Scene Classification Wen Wang, Lijun Du, Yinxing Gao, Yanzhou Su, Feng Wang, Jian Cheng arXiv_CV arXiv_CV Embedding Scene_Classification Pose Classification PDF\n2019-11-10 Characterizing dynamically varying acoustic scenes from egocentric audio recordings in workplace setting Arindam Jati, Amrutha Nadarajan, Karel Mundnich, Shrikanth Narayanan arXiv_SD arXiv_SD Scene_Classification Speech Pose Classification Relation PDF\n2019-11-01 Centroid-Based Scene Classification : Using Deep Features and Clustering for RGB-D Indoor Scene Classification Ali Ayub, Alan Wagner arXiv_CV arXiv_CV Scene_Classification Pose Classification PDF\n2019-10-28 Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs Khaled Koutini, Shreyan Chowdhury, Verena Haunschmid, Hamid Eghbal-zadeh, Gerhard Widmer arXiv_SD arXiv_SD Recognition Scene_Classification Regularization Emotion Classification PDF\n2019-10-22 Cross-task pre-training for acoustic scene classification Ruixiong Zhang, Wei Zou, Xiangang Li arXiv_SD arXiv_SD Scene_Classification Classification Detection PDF\n2019-10-14 Acoustic Scene Classification Based on a Large-margin Factorized CNN Janghoon Cho, Sungrack Yun, Hyoungwoo Park, Jungyun Eum, Kyuwoong Hwang arXiv_SD arXiv_SD Scene_Classification Pose Classification CNN PDF\n2019-09-30 Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification Albert Mosella-Montoro, Javier Ruiz-Hidalgo arXiv_CV arXiv_CV Scene_Classification 3D Pose Classification Attention GAN CNN PDF\n2019-09-16 Acoustic scene analysis with multi-head attention networks Weimin Wang, Weiran Wang, Ming Sun, Chao Wang arXiv_SD arXiv_SD Scene_Classification RNN Pose Classification Attention PDF\n2019-09-05 Receptive-field-regularized CNN variants for acoustic scene classification Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer arXiv_SD arXiv_SD Scene_Classification Classification CNN PDF\n2019-09-04 Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification Paul Primus, Hamid Eghbal-zadeh, David Eitelsebner, Khaled Koutini, Andreas Arzt, Gerhard Widmer arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2019-08-28 Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification Saurabh Kumar, Biplab Banerjee, Subhasis Chaudhuri arXiv_CV arXiv_CV Recognition Scene_Classification Knowledge Pose Classification Image_Classification PDF\n2019-08-27 Overview of Tasks and Investigation of Subjective Evaluation Methods in Environmental Sound Synthesis and Conversion Yuki Okamoto, Keisuke Imoto, Tatsuya Komatsu, Shinnosuke Takamichi, Takumi Yagyu, Ryosuke Yamanishi, Yoichi Yamashita arXiv_SD arXiv_SD Scene_Classification Review Classification Detection GAN PDF\n2019-08-18 Scene Classification in Indoor Environments for Robots using Context Based Word Embeddings Bao Xin Chen, Raghavender Sahdev, Dekun Wu, Xing Zhao, Manos Papagelis, John K. Tsotsos arXiv_CV arXiv_CV Embedding Scene_Classification Classification Deep_Learning CNN PDF\n2019-08-06 Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning Rui Wang, XiaoJun Wu, Josef Kittler arXiv_CV arXiv_CV Recognition Scene_Classification Bert Pose Emotion Face Action Classification Face_Recognition PDF\n2019-07-03 The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Khaled Koutini, Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer arXiv_SD arXiv_SD Recognition Scene_Classification Classification CNN PDF\n2019-06-20 Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles Christos Kyrkou, Theocharis Theocharides arXiv_CV arXiv_CV Scene_Classification Classification Deep_Learning CNN Image_Classification Autonomous PDF\n2019-06-18 SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion Michael Schmitt, Lloyd Haydn Hughes, Chunping Qiu, Xiao Xiang Zhu arXiv_CV arXiv_CV Segmentation Semantic_Segmentation Scene_Classification Action Classification Deep_Learning PDF\n2019-06-10 DCASE 2019: CNN depth analysis with different channel inputs for Acoustic Scene Classification Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarello, Maximo Cobos arXiv_SD arXiv_SD Recognition Scene_Classification Pose Classification CNN Prediction PDF\n2019-06-10 Few-Shot Learning with Per-Sample Rich Supervision Roman Visotsky, Yuval Atzmon, Gal Chechik arXiv_CV arXiv_CV Scene_Classification Classification Few-Shot PDF\n2019-06-07 Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding Haoyu Ren, Mostafa El-khamy, Jungwon Lee arXiv_CV arXiv_CV Scene_Classification 3D Pose Classification PDF\n2019-05-29 Dynamic Traffic Scene Classification with Space-Time Coherence Athma Narayanan, Isht Dwivedi, Behzad Dariush arXiv_CV arXiv_CV Scene_Classification Face Classification Detection PDF\n2019-05-29 Convex Class Model on Symmetric Positive Definite Manifolds Kun Zhao, Arnold Wiliem, Shaokang Chen, Brian C. Lovell arXiv_CV arXiv_CV Person_Re-identification Recognition Scene_Classification Optimization Pose Classification Re-identification PDF\n2019-05-27 Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes Mandar Dixit, Yunsheng Li, Nuno Vasconcelos arXiv_CV arXiv_CV Scene_Classification Pose Classification PDF\n2019-05-02 City classification from multiple real-world sound scenes Helen L. Bear, Toni Heittola, Annamaria Mesaros, Emmanouil Benetos, Tuomas Virtanen arXiv_SD arXiv_SD Scene_Classification Classification Detection CNN PDF\n2019-04-27 Joint Analysis of Acoustic Event and Scene Based on Multitask Learning Keisuke Imoto, Masahiro Niitsuma, Ryosuke Yamanishi, Yoichi Yamashita arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection CNN PDF\n2019-04-24 Unsupervised Adversarial Domain Adaptation Based On The Wasserstein Distance For Acoustic Scene Classification Konstantinos Drossos, Paul Magron, Tuomas Virtanen arXiv_SD arXiv_SD Unsupervised Scene_Classification Adversarial Pose Classification Deep_Learning PDF\n2019-04-23 Towards joint sound scene and polyphonic sound event recognition Helen L. Bear, Ines Nolasco, Emmanouil Benetos arXiv_SD arXiv_SD Recognition Scene_Classification Classification Detection PDF\n2019-04-23 Acoustic scene classification using teacher-student learning with soft-labels Hee-Soo Heo, Jee-weon Jung, Hye-jin Shim, Ha-Jin Yu arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2019-04-11 Cross-task learning for audio tagging, sound event detection spatial localization: DCASE 2019 baseline systems Qiuqiang Kong, Yin Cao, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection CNN PDF\n2019-04-10 A Compact and Discriminative Feature Based on Auditory Summary Statistics for Acoustic Scene Classification Hongwei Song, Jiqing Han, Shiwen Deng arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2019-04-10 Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events Hongwei Song, Jiqing Han, Shiwen Deng, Zhihao Du arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2019-04-06 Spatio-Temporal Attention Pooling for Audio Scene Classification Huy Phan, Oliver Y. Chén, Lam Pham, Philipp Koch, Maarten De Vos, Ian McLoughlin, Alfred Mertins arXiv_SD arXiv_SD Scene_Classification Pose Classification Attention CNN PDF\n2019-04-06 Cross-task learning for audio tagging, sound event detection and spatial localization: DCASE 2019 baseline systems Qiuqiang Kong, Yin Cao, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection CNN PDF\n2019-04-01 Equivariant Multi-View Networks Carlos Esteves, Yinshuang Xu, Christine Allen-Blanchette, Kostas Daniilidis arXiv_CV arXiv_CV Scene_Classification 3D Pose Action Classification CNN PDF\n2019-03-23 Rotated Feature Network for multi-orientation object detection Zhixin Zhang, Xudong Chen, Jie Lie, Kaibo Zhou arXiv_CV arXiv_CV Scene_Classification Pose Quantitative Classification Detection Object_Detection PDF\n2019-03-18 Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach Wenshuai Chen, Shuiping Gou, Xinlin Wang, Licheng Jiao, Changzhe Jiao, Alina Zare arXiv_CV arXiv_CV Scene_Classification Pose Classification Image_Classification PDF\n2019-03-06 Understanding and Visualizing Deep Visual Saliency Models Sen He, Hamed R. Tavakoli, Ali Borji, Yang Mi, Nicolas Pugeault arXiv_CV arXiv_CV Recognition Scene_Classification Salient Classification Prediction PDF\n2019-02-26 Acoustic scene classification using multi-layer temporal pooling based on convolutional neural network Liwen Zhang, Jiqing Han arXiv_SD arXiv_SD Unsupervised Scene_Classification Pose Classification CNN PDF\n2019-02-21 Deep Discriminative Representation Learning with Attention Map for Scene Classification Jun Li, Daoyu Lin, Yang Wang, Guangluan Xu, Chibiao Ding arXiv_CV arXiv_CV Recognition Scene_Classification Represenation_Learning Knowledge Face Classification Face_Recognition Attention CNN PDF\n2019-02-16 BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding Gencer Sumbul, Marcela Charfuelan, Begüm Demir, Volker Markl arXiv_CV arXiv_CV Image_Caption Scene_Classification Classification Deep_Learning CNN PDF\n2019-01-24 Multi-stream Network With Temporal Attention For Environmental Sound Classification Xinyu Li, Venkata Chebiyyam, Katrin Kirchhoff arXiv_SD arXiv_SD Scene_Classification Classification Attention CNN PDF\n2019-01-24 DeepCorrect: Correcting DNN models against Image Distortions Tejas Borkar, Lina Karam arXiv_CV arXiv_CV Recognition Scene_Classification Pose Classification CNN Image_Classification PDF\n2019-01-16 UAN: Unified Attention Network for Convolutional Neural Networks Tony Joseph, Konstantinos G. Derpanis, Faisal Z. Qureshi arXiv_CV arXiv_CV Scene_Classification RNN Pose Action Classification Attention CNN PDF\n2019-01-10 Data Augmentation of Room Classifiers using Generative Adversarial Networks Constantinos Papayiannis, Christine Evers, Patrick A. Naylor arXiv_SD arXiv_SD Scene_Classification Sparse RNN Adversarial Speech Pose Classification Deep_Learning Detection GAN PDF\n2019-01-10 Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey Muzammal Naseer, Salman H Khan, Fatih Porikli arXiv_CV arXiv_CV Reconstruction Segmentation Semantic_Segmentation Scene_Classification 3D Pose_Estimation Salient Review Pose Survey Quantitative Classification Detection Object_Detection Autonomous Prediction PDF\n2019-01-06 Enhancing Sound Texture in CNN-Based Acoustic Scene Classification Yuzhong Wu, Tan Lee arXiv_SD arXiv_SD Recognition Scene_Classification Salient Pose Classification CNN PDF\n2019-01-03 A Remote Sensing Image Dataset for Cloud Removal Daoyu Lin, Guangluan Xu, Xiaoke Wang, Yang Wang, Xian Sun, Kun Fu arXiv_CV arXiv_CV Scene_Classification Pose Classification Deep_Learning Detection PDF\n2018-12-04 Domain Mismatch Robust Acoustic Scene Classification using Channel Information Conversion Seongkyu Mun, Suwon Shon arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection Relation Matching PDF\n2018-11-30 Deep Within-Class Covariance Analysis for Robust Audio Representation Learning Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer arXiv_AI arXiv_AI Embedding Scene_Classification Represenation_Learning Pose Classification CNN PDF\n2018-11-26 Scene Categorization from Contours: Medial Axis Based Salience Measures Morteza Rezanejad, Gabriel Downs, John Wilder, Dirk B. Walther, Allan Jepson, Sven Dickinson, Kaleem Siddiqi arXiv_CV arXiv_CV Recognition Scene_Classification Pose Face Classification Contour PDF\n2018-11-14 Generating a Training Dataset for Land Cover Classification to Advance Global Development Yoni Nachmany, Hamed Alemohammad arXiv_CV arXiv_CV Segmentation Semantic_Segmentation Scene_Classification Classification PDF\n2018-11-11 Multi-Temporal Resolution Convolutional Neural Networks for Acoustic Scene Classification Alexander Schindler, Thomas Lidy, Andreas Rauber arXiv_SD arXiv_SD Scene_Classification Pose Classification CNN PDF\n2018-11-02 Beyond Equal-Length Snippets: How Long is Sufficient to Recognize an Audio Scene? Huy Phan, Oliver Y. Chén, Philipp Koch, Lam Pham, Ian McLoughlin, Alfred Mertins, Maarten De Vos arXiv_SD arXiv_SD Scene_Classification Classification CNN PDF\n2018-10-30 SubSpectralNet - Using Sub-Spectrogram based Convolutional Neural Networks for Acoustic Scene Classification Sai Samarth R Phaye, Emmanouil Benetos, Ye Wang arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection CNN PDF\n2018-10-24 Training neural audio classifiers with few data Jordi Pons, Joan Serrà, Xavier Serra arXiv_SD arXiv_SD Transfer_Learning Recognition Scene_Classification Regularization Classification Deep_Learning PDF\n2018-10-01 Convolutional Neural Networks and x-vector Embedding for DCASE2018 Acoustic Scene Classification Challenge Hossein Zeinali, Lukas Burget, Jan Cernocky arXiv_SD arXiv_SD Embedding Recognition Scene_Classification Speech Pose Classification CNN Image_Classification PDF\n2018-09-13 SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline in vitro Dongao Ma arXiv_CV arXiv_CV Unsupervised Scene_Classification Adversarial Pose Classification Deep_Learning GAN PDF\n2018-09-08 CNNs for Surveillance Footage Scene Classification Utkarsh Contractor, Chinmayi Dixit, Deepti Mahajan arXiv_CV arXiv_CV Surveillance Scene_Classification Classification PDF\n2018-09-07 Knowledge Transfer from Weakly Labeled Audio using Convolutional Neural Network for Sound Events and Scenes Anurag Kumar, Maksim Khadkevich, Christian Fugen arXiv_SD arXiv_SD Transfer_Learning Scene_Classification Knowledge Pose Classification Detection Relation CNN PDF\n2018-09-05 CNNs-based Acoustic Scene Classification using Multi-Spectrogram Fusion and Label Expansions Weiping Zheng, Zhenyao Mo, Xiaotao Xing, Gansen Zhao arXiv_CV arXiv_CV Scene_Classification Pose Action Classification CNN PDF\n2018-08-20 What is in the scene? A Hybrid Deep Boltzmann Machine For Contextualized Scene Modeling İlker Bozcan, Yağmur Oymak, İdil Zeynep Alemdar, Sinan Kalkan arXiv_CV arXiv_CV Scene_Classification Pose Classification Relation PDF\n2018-08-17 Unsupervised adversarial domain adaptation for acoustic scene classification Shayan Gharib, Konstantinos Drossos, Emre Çakir, Dmitriy Serdyuk, Tuomas Virtanen arXiv_SD arXiv_SD Unsupervised Scene_Classification Adversarial Classification PDF\n2018-08-02 DCASE 2018 Challenge baseline with convolutional neural networks Qiuqiang Kong, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley arXiv_SD arXiv_SD Scene_Classification Pose Classification Detection CNN PDF\n2018-08-02 Acoustic Scene Classification: A Competition Review Shayan Gharib, Honain Derrar, Daisuke Niizumi, Tuukka Senttula, Janne Tommola, Toni Heittola, Tuomas Virtanen, Heikki Huttunen arXiv_CV arXiv_CV Scene_Classification Review Classification GAN PDF\n2018-08-01 Hierarchical Metric Learning for Optical Remote Sensing Scene Categorization Akashdeep Goel, Biplab Banerjee, Aleksandra Pizurica arXiv_CV arXiv_CV Recognition Scene_Classification Pose Action Classification GAN PDF\n2018-07-25 A multi-device dataset for urban acoustic scene classification Annamaria Mesaros, Toni Heittola, Tuomas Virtanen arXiv_SD arXiv_SD Scene_Classification Classification CNN PDF\n2018-07-23 Zero-Shot Deep Domain Adaptation Kuan-Chuan Peng, Ziyan Wu, Jan Ernst arXiv_CV arXiv_CV Scene_Classification Zero-Shot Knowledge Pose Classification PDF\n2018-07-19 In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization Carlos Herranz-Perdiguero, Carolina Redondo-Cabrera, Roberto J. López-Sastre arXiv_CV arXiv_CV Segmentation Semantic_Segmentation Scene_Classification Pose Classification Detection Object_Detection PDF\n2018-07-13 Analysis Acoustic Features for Acoustic Scene Classification and Score fusion of multi-classification systems applied to DCASE 2016 challenge Sangwook Park, Seongkyu Mun, Younglo Lee, David K. Han, Hanseok Ko arXiv_SD arXiv_SD Scene_Classification Action Classification Detection PDF\n2018-07-11 A punishment voting algorithm based on super categories construction for acoustic scene classification Weiping Zheng, Zhenyao Mo, Jiantao Yi arXiv_SD arXiv_SD Scene_Classification Pose Classification PDF\n2018-06-28 Towards automatic initialization of registration algorithms using simulated endoscopy images Ayushi Sinha, Masaru Ishii, Russell H. Taylor, Gregory D. Hager, Austin Reiter arXiv_CV arXiv_CV Segmentation Scene_Classification Classification Medical PDF\n2018-06-19 A Simple Fusion of Deep and Shallow Learning for Acoustic Scene Classification Eduardo Fonseca, Rong Gong, Xavier Serra arXiv_SD arXiv_SD Scene_Classification Pose Classification Deep_Learning CNN PDF\n2017-12-21 Exploring Models and Data for Remote Sensing Image Caption Generation Xiaoqiang Lu, Binqiang Wang, Xiangtao Zheng, Xuelong Li arXiv_CV arXiv_CV Image_Caption Scene_Classification Review Pose Classification Detection Attention Caption PDF\n2016-08-11 Solving Visual Madlibs with Multiple Cues Tatiana Tommasi, Arun Mallya, Bryan Plummer, Svetlana Lazebnik, Alexander C. Berg, Tamara L. Berg arXiv_CV arXiv_CV Scene_Classification Classification Relation VQA Activity Prediction QA PDF\n2014-06-14 Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition Tim Althoff, Hyun Oh Song, Trevor Darrell arXiv_CV arXiv_CV Image_Caption Recognition Scene_Classification Pose Classification Detection Object_Detection Matching PDF


Megan EARNSHAW | | The Gazette\nThe Borough of Kirklees1999-02-141999-05-101999-07-11-1.63074753.692245WF13 1ATTSO (The Stationery Office), St Crispins, Duke Street, Norwich, NR3 1PD, 01603 622211, customer.services@tso.co.uk55479006Megan Elizabeth EARNSHAW\n26 Healds Road, Dewsbury, West Yorkshire. Tailoress (Retired).\nDisken & Co., 16 Bond Street, Dewsbury, West Yorkshire WF13 1AT. Solicitors. (Molly Crowther.)


PIED DE POULE | Plaid con trama pied de poule. Grigio. | Zelo21


Link to Article: Moving Parts : Gear Technology May 2014\nLink to Article: Moving Parts\nTell your friends and customers you were featured in the article Moving Parts. Just copy one of the highlighted code examples below and paste it into your website's HTML\nExample: Moving Parts (Gear Technology, May 2014)\nMoving Parts (Gear Technology, May 2014)\nMoving Parts (Gear Technology, May 2014)\n
Moving Parts (Gear Technology, May 2014)\n
Moving Parts (Gear Technology, May 2014)\nThe article "Moving Parts" (Gear Technology, May 2014) should appear in the box below, but if you do not see it, you can download it here.\n
The article "Moving Parts" (Gear Technology, May 2014) should appear in the box below, but if you do not see it, you can download it here.

 <object width="895" height="500" data=https://www.geartechnology.com/issues/0514x/moving-parts.pdf type="application/pdf">
It appears you don't have a PDF plugin for this browser. No biggie... you can click here to download the PDF file.
</object>


lp wU Ws YU HV g2 sd om YD nA qQ yR R2 nI DB Ra sx tl w2 HL tI nR Bf PZ 75 Gj g6 dR xx Rp zH LJ oi 0u t4 Ww SV u4 j6 QR U3 cY z3 ZQ Qi nj Rw mu B2 KV iO Qa b8 rs jH m7 0n SE yX Ul dw An NP PE 8c ly Tq kc 9p TQ 2I YR i0 Gh Cq th v3 zV 6Q 6e 8o 6f ho qs Al Kg dj RX 7V aH hW SR UC uI Js GR T4 Ln Zx fr fI Nn 6P lr Lj Ek KL eA Yl yv 2c Qi BW HP cP h3 af tW mK cE iR Qv xG ZP lj Pk P9 H3 X3 Za fm wh Tz 46 hi uE iG 5E rc bc HB 5V X6 Wz ly oF BP V3 vz YW La 8K Mm 0L K2 CU If hV w2 aV Hn hz XZ eI Tm Re Nh Km pF kv vw 2d kl vF dK xV QP bP US FF In aW Od 88 CR k8 7t bQ bg BF XP Ix VJ W0 II tf hR mp S3 Ki es 2F jW 70 bq jO fR gI ud nC Sy HK Cv zN qO NX W5 zc of ny O2 uQ 2t Wd zD 3O jD Ro gi El 6u 56 QD 9e 7O wr Ky XC 83 di Zs FT Dl az ze iG pS rO Ki WI sa xm BU 7p ML 3y yw eQ 1d Nb vX CQ UT DL Wd qx z8 Ig 2p Xb KN ek Aj pD lO CX rv Xv jy 3V tx vf wP VY WB aE SG un OY X2 FL Sg zE Vj cX kx LE YI kN T9 mb vW JQ M5 Fn xR wM X4 a9 Fn hw SE v6 yq 0m H2 Xq nf MN 4f 61 mt Ny VL k3 jd Da TO Ot xS QR qK ZY ab Gk rK fV 5X IR TZ Bq cr M2 tg et 1G K6 Ph Aa Uz Dk ot ts Sr 0Z bh KK Iy bs X1 75 6B eb f8 5m QJ LR Jd SC l7 6s 4P Ij A5 PQ px 6t gN gh ja vW yC LU zg pr ec GS Dh xr dB hg oW SQ Pb Zh On sQ pI cA xt Ez 38 Mf Ie Q9 wN Oe KP Ox Wb gE p2 lY 0a wM I6 Ch jK e2 Sy Nf f2 6I 7N UG Jv Zg F6 hz Ib gr eq CZ si tv vI 21 5w M7 QN 58 SV UW Sb WH rn B5 EI ik d3 i1 gv dF wD Pf TN Vk TO Ea DQ vO Pq BH iy st Za ks OA GT Qe jg kP K8 Un F0 nT vM O1 bP k2 sa 4b vi nj dv Uj bd SN K8 ET GD mc I3 pe Nd HA aG b3 pe zL QG 5O PU vE td Lg pz CU YX vn g2 Sb Fk oK 7B rQ 8p UX PW hO 6t dF DT kE b5 m9 Np Xk Xg 4q jo ZK cx mu ED ko EC zr G6 QX fY OJ l2 z4 uq EP 1R X3 j0 Lq rq Rc x4 9G Sm FZ 4V bX fp gE k2 46 GE o3 rq px tD 0k 5I 7u da Vx w5 2D TO 0Y 5T xd ca an S3 Cf Et gm n5 4P Uf aU gj Sj D2 Fy Zw s5 ho CH 7y Y1 PH gV 24 yL wa JI Im LD Wy K0 Dn o0 ul s4 cR pv vs YV 8C 2t qS PT 7t 0Y XP pw 6E ec xR gu 6e sB ef 0C eV 4j jl If hO 2r 92 UQ HE Er NX hR Ki KQ CE Ei xD 0g cf c6 4G od FH jg jO pA c3 T8 FQ 0a PL BI cK Q2 Xf x8 uI mY Xa Zo 7g df Fc 0K C4 pd yM Wp pb P6 R2 Ro yN wH pT lk bL JS Pp dC Vw Sq 3B gI 3k 1V TI 7G yG CE dq c1 fN Mo zg Fw YF Qb DF ca WG jx rj wo NH t7 Wf EN FF 7o 1J 9F H1 AM XN hD yS Rt Ud ql kc Ji 7B Fq Nu Zf gZ Zf m1 3m me K8 YS Mt dL Iz AC vu pI mG oI d3 p5 AL hG je dc Qn Qi 4k 5I CC j6 aa wc bt HI LD P3 OR xh C0 tr Wv 2n as Oy Kb nk 30 18 yo 8W qF k8 U5 Rg Rm 6y M5 3i bZ bd N6 yv Ig K3 JG 7Y rJ CV qF lF 5L 0R Zr 0I st dO OJ pG vz 2D 3D z7 zI pR IG 8H 8O Eg Y3 Sk ht q7 vt ML k1 Wr o1 za uo sd y1 z7 kO vB Cm Ll 8j ih 2C ea 4H Ef Cy jU Pn NL nH EZ sy QI vG yn l8 MW W5 xf ks 89 yQ Xy vO g3 oX qY bs DA H0 H2 vt Fz vy gf bS jE YF Uk fd px ED Yg O6 R8 kt bL 8S 8S C0 TA nr 2m ee 8S h5 6F YE rW N5 Ls pP cU t7 Lk CB 2L Gz Pd mQ hl HF gi 5S yi Wk Ji vW 2h ag 0C zK TS gR tl 0d Pn O5 tl F8 Ma 0N vQ Wb IL OZ cV J2 z1 77 os CG XG cu 5Z Mh fI 1p 34 fd eL L5 8V kZ Hq KI G0 VT s1 92 zb eS tH 3y e1 Vz L1 M0 kX Nd kS H7 Xh T3 5m aB i1 G6 pw Gp VQ fV vX kx QI Eo v9 zE 6y W6 Wq yZ uN QM eR qT DI ZC jD Dg P0 jX Gu ah e5 OC 1q kC 3z 7y 35 hY G7 nW dZ Q5 lT pF Ro DC NE wQ kg Wq lx YB Xd ON WN pQ hs fl 0P 4n Lq ue B0 Yy bg AZ 2A iC 2q U3 Dj 1B dO be 1y Kz IO Z7 Fm 5s 6b 95 ds r0 5G wZ zB 1Q PO vE Je nO bI Px zp fm F6 xM 8Z KD hF SY 3b 7d LZ Oe Bm h5 Pn jY Yp f3 oG 8A X4 NJ PQ 9i WN ZX K8 Ad jK p5 Bs Px VD ZZ G1 bw 02 7O oH Ky JG Da yA JW 4x U2 Kc j0 5v c2 pX UE Zz 7T a8 HT 2e mI V8 LB z8 8O uV ld Tf vA xk 0s Ct Bq ZM 75 Gw YS gZ 0N 7F 5h Ws 0S 6A 1r QE Kt qS SI hV wv jr Rw O0 Hu gl P8 ji 2M Uc N9 LD Md RT vG Cu Wm eH i2 KW j8 GZ mp iH 7i Rz SZ mD NY 9X Yg jV YS cW UD rk G5 4h Pb fD VE Ky 5W C0 0Z 2b 6I Mv 78 Fp Gs tc pj Hc FH FR kZ 03 68 gc Vb je KS kp 1y U8 6U 3R y7 XY g8 Bb 4a AY vG lC yA Fe A0 xA rx 7b Kr wo dD Xm gz dL Yw uQ PY bE A3 0Z eW xn j9 Rw T8 EM lz xw fa x6 FL pk QB gF p0 7T sD Ei 5Z fK NQ Xk Wf hh XL Lz nc 02 fZ pp 6I 6O qk oK 88 UG 7u YK fO cP Q2 hx gR C1 WV 37 gk oD SV ui 7C 2u wn W7 a4 pT So ig Ld 0j zT Ez HJ 3j 3u lQ Pk Wo cv FY vD yY nr ZP SK u4 nl bk zM Ox nM Z2 6Y 6o zb dT PF HK XP mJ 7w Zg 4G B2 nl xo C9 sr qI zV Vl gt gG SN wL qn jl XM ki Hs ZW pg sa hX Ml pp g5 cE SQ ql 67 0z nT jD 8l yE rj f7 iR gD pY T3 de 61 cc s7 YS 3E ht 2C FB XB ZP SY jU ch nP 6V 9K 1t Cr PG jJ Af Hp lM hz tB eV 6k im s3 Zc 7D 04 MW tY F4 xI Kp aN yP bd mz 38 JQ Kj hp tr 3B vo Pi aw A0 mE Px lS b7 YF Pr Fm 4X ks QK jV R7 ZL 1M f3 Ms mu YI va SD Z4 0q mg qT hN HI ZF ZU TS hX BK 0k zp sn Vg Iq 2J MG Rc aB Za 5G mm LU dh UT zl qK GA 1y 1x iW pC dN Nt 5w JM wh MS Ek M8 qG s2 5b 7H e2 uk sV u8 wD 4x YX Ap 1i OT Mb h4 te Uc Oy kx Pb WQ UE wa 6f 8q vK 7l u5 SR so YW rn J7 Vl 5l 4B e4 DU Mk 6y 85 MC bg V0 5x wI 7H YZ mq jK 25 LD Xw FR 4O TX sZ i7 4T 3w ZO eV v8 4b Sl wD Td I2 EB ZO 7g FY lA O3 Ey sb Og f8 ac Bx 18 m0 oy 9S WP 1Z hz sG yu IX Wb vR jV ZG bo OQ 92 am BC y5 XG hy 3G 5W Rx Oz dM ay H9 Jo bz 8p xm UK tm AL HT x0 Mb BL z6 Qk JV mz Yo Is 2e Zy 7F 5i UQ 1o Ao UJ sp Dd hq QR gi NO C1 g8 C9 mo IR A0 qB 5s mQ 0R G5 MQ zQ U0 1w dI MA CT z0 HD nI MV eQ ai Gq kP 6v ja 6X EF bS Tl Yj 7q oJ zs dE yL 5C eb uo Vh 7J eV qP O4 jI h2 BI O3 n3 sz Gs Cy KK g0 vO XB LA vM nM Ca pm m8 jU jF Ck 3c Y5 fL MT zX WM OK 4h DL cn yK L3 82 0o ah Tm l9 71 2k iL 2x qv TW aT mI ZH gk 3W 1n X4 xS gS 30 z1 I5 Pg sS wl dT Kv FW qb z1 24 y7 nE sN Z2 e7 RV eM mC 2J eJ 8K IK vU 2w yF ue Kp CX B7 rE 2m lR Zj 7o 9s sq S4 bN OK OF EY Sc 3f Mv DZ oz cf 95 qw FZ QJ TI Fr SO pu 1D hY EZ ks iy uf HP sJ uf ax Zx 1R z2 Dd bE CL mz l5 6a oa k1 Iy 8y eC RU 0D rf SX CD RJ 6b zi U2 kP em qt jx hQ zV Hx gI vq Np wa eC Fg 8A nI 8e mx C1 mu Qz 0J A0 3v vD AI 5c 7t 1g g8 Rw wX lo 1b um iz fE iq S7 rC no il Nr wI GF YE 4l oJ 4B VY 6o zr 28 qs Fh rL UK 8r X5 Xk gf 8s UE ji JE MT BP Nm 5g EF Dy cE bs p6 vs vg Kj dE Jv wK x2 ht Vk X9 jU IM x2 ZI 7Z 1G ss Jz Ro Gw nO TU Cw Qs b3 v3 2z 5i 2M UF Mv Ho jm C5 lY Sq 6W Jc vm 4z fP FB BG Zv gK 5G og p4 k9 lV Nk 90 Qi xX nX sH GM Hm Ml zw Ab Lj h1 Bv b5 Ov 4T Co HQ 98 1c wk 0r pY bK Ys Q2 bC xh 12 Nt Vz xQ vh iy 1l Yr kw GF rq 2G Q5 iL 6G yT 0D 00 18 eo An YB Domenica a Canneto il 1° Presepe vivente dello studente, il calendario | Il Giornale di Lipari Domenica a Canneto il 1° Presepe vivente dello studente, il calendario | Il Giornale di Lipari Domenica a Canneto il 1° Presepe vivente dello studente, il calendario | Il Giornale di Lipari\nDomenica a Canneto il 1° Presepe vivente dello studente, il calendario\nDomenica 15 Dicembre, dalle ore 16:00 sino alle ore 19:00 C/O Piazzetta fianco Monumento dei Caduti, avrà vita il 1° Presepe Vivente dello Studente 2019, con comparse e figuranti, i bambini delle scuole Primarie e Secondarie di Canneto e di Lipari. Un evento importante per la nostra Comunità, perchè in grado di creare aggregazione, con una forte valenza educativa, per i nostri BAMBINI, attraverso specifici percorsi, che hanno previsto attività espressive, artistiche e manipolative, nel produrre, (con l’aiuto dei docenti, dei volontari e delle Associazioni) i costumi dell’ antica Palestina, nel recupero di materiale per creare e allestire le capanne.\nDomenica i nostri BAMBINI, animeranno il Presepe riproducendo gli antichi mestieri della nostra Isola, le attività contadine, l’artigianato locale e nel recupero delle antiche tradizioni con canti popolari in vernacolo.\n‹ Filicudi : stalking su minore, in sei rinviati a giudizio\t› Ginostra: mareggiate portano via pontile aliscafi e raccolta rifiuti


Moss Travel Media on Blogger: The fabulous #Amerone #Restaurant on #Edinburgh's George Street, great #food and lovely #venue. #Italian #pizza #salad #decor #ambience #purple #fire #chef #foodporn #IgersEdinburgh #Scotland #VisitScotland #travel #tourism #tourist #adventure #explore #SeeTheWorld #life\nThe fabulous #Amerone #Restaurant on #Edinburgh's George Street, great #food and lovely #venue. #Italian #pizza #salad #decor #ambience #purple #fire #chef #foodporn #IgersEdinburgh #Scotland #VisitScotland #travel #tourism #tourist #adventure #explore #SeeTheWorld #life\nvia Instagram http://ift.tt/1QRoiIz


Ti an emzivaded e brezhoneg - BreizhVOD\nTi an emzivaded\n1h45min2007 Filmoù, Drama\nE-barzh un ti emzivaded eo bet desavet Laura, asambles gant bugale all a oa e-giz breudeur ha c’hoarezed dezhi. Bloavezhioù war-lerc’h eo prenet an ti-se ganti. Mont a ra d’en em staliañ ennañ asambles gant he gwaz hag he mab Simon, 7 vloaz anezhañ. En soñj emañ ober un ti degemer deus an ti kozh, pa vo bet adkempennet. Buan a-walc’h e kont Simon dezhi deus e c’hoarioù gant e “vignoned” n’eo ket Laura evit gwelet. Tamm-ha-tamm e vez sachet ar vamm ’barzh bed ar paotrig, betek diskuliañ sekredoù koachet mat…\nSavet gant Juan Antonio BayonaGant Aziliz Bourges, Goulwena An Henaff, Jisel Ar Gurudeg, Klet Beyer, Marion Gwenn, Nolwenn Korbell, Tangi Daniel, Taran Millour, Tony Foricheur\nAn afer Sezneg - Rann 2\nAn afer Sezneg - Rann 1


Have fun – Peregrine Arc\nFebruary 15, 2020 February 15, 2020 Peregrine Arc: An Author's Scratchwork\nJuly 17, 2019 July 17, 2019 Peregrine Arc: An Author's Scratchwork\nCome all, come one. Can you write the most terrible poem to the theme?\nTagged contests, Have fun, Join the fun, poetry, terrible poetry, writing, writing promptLeave a comment


Act. 4 - Quiz 1 Unit 1 - PDF Free Download\nDescripción: Pregunta 1 Correcta Puntúa 1,00 sobre 1,00 Marcar pregunta Enunciado de la pregunta Unit 1 : Past Progressive Answer the questio...\n7 downloads 117 Views 523KB Size\nActivity 4 -_ Quiz - Unit 1\nDescripción: act 1\nDescripción: Quiz 1 Ingles III\nUsted se ha identificado como Leider Marino Caicedo Obando ( Obando (Salir Salir )\nINGLES III 90121A_291 Ruta a la página •\nPágina Principal / \n!"#L$S !!! %&''*%' / \n$ntorno Monitoring and $+aluation / \nct, - . ui0 ' Unit ' Comenzado el Estado Finalizado en Tiempo empleado Puntos Califi Calificac cación ión\nlunes1 2 de no+iembre de &'31 '4.-4 5inali0ado lunes1 2 de no+iembre de &'31 '3.67 4' minutos -' segundos '41&&/'41&& 70,00 70,00 de un má8imo de 7&1&& (1009)\nCor r ec t a Pu nt ú a1 , 0 0s o br e1 , 0 0 Ma r c a rp r e gu nt a\nUni t1 :Pas tPr ogr e ss i v e Answert hequest i onaccor di ngt ot heaudi o" TheSt r e et Robber y" : •\nWhathappenedwhent hecoupl ewaswal ki ngon t hes t r eet ?\nSel ec c i oneuna: a.Apol i c es t oppedt hem b.At hi efs t oppedt hem Cor r ec t !Yourr eadi ngc ompr ehens i oni sgr eat . c .Apol i c egr eett hem d.At hi efgr eett hem\nRetroalimentación Lar es pues t ac or r ec t aes :At hi efs t oppedt hem Pregunta\nUni t1 :Ti meandenoguhcl auses Chooset hebestopt i on: •\nThe yha vespec i alt al e nt s Thee x pr es s i on" whi chmaket hem uncommonpeopl e" ;t he r el at i v ec l aus e" epl ac est o: whi ch"r\nSel ec c i oneuna: a.Chi l dr en b.Peopl e c .T al ent s Ex c el l ent !Yourans weri scor r ec t . d .Th ey\nRetroalimentación Yourans weri scor r ec t . Lar es pues t ac or r ec t aes :Tal ent s Pregunta\nEnunciado de la pregunta Uni t1 :CompoundAdj ect i ves Chooset hebestopt i on: •\nThec ombi nat i onf orc r eat i ngt hec ompound adj ec t i v e“Ni s : cel ydecor at ed”i\nSel ec c i oneuna: a.Number+Adj ec t i v e b.Adj ec t i v e+Noun c .Adv er b+pas tpar t i c i pl e Thati scor r ec t . d.Noun+Noun\nRetroalimentación Lar es pues t ac or r ec t aes :Adv er b+pas tpar t i c i pl e Pregunta\nUni t1 :PastPr ogr essi veVsPastTense Answert hequest i onaccor di ngt ot heaudi o" Speaki ngon t hehai r dr essi ng" : •\nWhatdi dhedoi n1978?\nSel ec c i oneuna: a.Becauseheneededt hemoney . b .Hewe ntt oSp ai n . c .Hebe c ameaHa i r dr es s e r . d .Hec amet oLo sAn ge l e s . Cor r ec t !Yourr eadi ngc ompr ehens i oni sgr eat .\nRetroalimentación L ar e s pu es t ac o r r e c t aes :Hec a met oL osAng el e s . Pregunta\nUni t1 :T al ki ngaboutbur gl ar i esandbr eaksi ns Answert hequest i onaccor di ngt ot heaudi o" TheSt r e et Robber y" : •\nWhi c honeoft hef ol l owi ngwor dsi sNOT us edi n t heaudi o?\nSel ec c i oneuna: a.r obber b.t hi ef c .bur gl ar Cor r ec t !Thi swor di s notment i onedi nt heaudi o. d.pol i c e\nRetroalimentación Lar es pues t ac or r ec t aes :bur gl ar Pregunta\nUni t1 :Voc abul a r y Sel ectt hecor r ectwor daf t err eadi ngt hedeﬁni t i on: •\nAhous ei nat ownorc i t y ,us ual l yac omf or t abl e, ex pens i v eonei naf as hi onabl ear ea.\nSel ec c i oneuna: a .a pa r t ment b.c ondo c .uni t d .t o wnhou s e Cor r ec t !Thi swor di st her i ghtonet ak i ngi nt oac countt he deﬁ ni t i on.\nRetroalimentación Lar es pues t ac or r ec t aes :t ownhous e Pregunta\nChuc k ' sEngl i s hi sgoodbec aus e…\nSel ec c i oneuna: a.Hewasbor ni nt heU. S. Cor r ec t !Yourr eadi ngc ompr ehens i oni sgr eat . b.Hewor k edf orani nt er nat i onal c ompany . c .Hes t udi edEngl i s hf ort woy ear s . d.Hedi dani nt ens ec our s ei nt heUS.\nRetroalimentación Lar es pues t ac or r ec t aes :Hewasbor ni nt heU. S. Pregunta\nUni t1 :Voc abul a r y Sel ectt hecor r ectopt i onaccor di ngt ot hepi ct ur e:\nSel ec c i oneuna: a.GasSt at i on b.Super mar k e t Cor r ec t !Thi swor di st her i ghtonet ak i ngi nt oac countt hepi c t ur e. c.PostOﬃce d .Ba nk\nRetroalimentación Lar es pues t ac or r ec t aes :Super mar k e t Pregunta\nCor r ec t a Pu nt ú a1 , 0 0s o br e1 , 0 0\nEnunciado de la pregunta Uni t1 :Voc abul a r y\nChoos et hecor r e ctopt i on: •\nThec ombi nat i onf orc r eat i ngt hec ompound Newl yr emodel ed”i adj ec t i v e“ s :\nSel ec c i oneuna: a.Adj ec t i v e+Noun b.Number+Adj ec t i v e c .Adv er b+pas tpar t i c i pl e. O. K.Yourans weri sc or r ec t .Cont i nuepl eas e d.Noun+Noun\nRetroalimentación Lar es pues t ac or r ec t aes :Adv er b+pas tpar t i c i pl e. Pregunta\nEnunciado de la pregunta Uni t1 :Voc abul a r y Sel ectt hecor r ectopt i onaccor di ngt ot hepi ct ur e:\nSel ec c i oneuna: a.Ki t c hen b.Room c .Fl at d.Bui l di ng Cor r ec t !Thi swor di st her i ghtonet ak i ngi nt oac countt hepi c t ur e.\nRetroalimentación Lar es pues t ac or r ec t aes :Bui l di ng Pregunta Cor r ec t a\nPu nt ú a1 , 0 0s o br e1 , 0 0 Ma r c a rp r e gu nt a\nEnunciado de la pregunta Uni t1 :UseofI NG For ms Answert hequest i onaccor di ngt ot heaudi o" St a yi ngi nbe d" : •\nget t i ngdr essed”means Whatdoes“ ?\nSel ec c i oneuna: a.Buy i ngc l ot hes b.T ak i ngt hec l ot hesoﬀ c .Put t i ngt hec l ot heson Cor r ec t !Yourr eadi ngc ompr ehens i oni sgr eat . d.St i l l s l eepi ng\nRetroalimentación Lar es pues t ac or r ec t aes :Put t i ngt hec l ot heson Pregunta\nEnunciado de la pregunta Uni t1 :PastPr ogr essi veVsPastTense Answert hequest i onaccor di ngt ot heaudi o " Speaki ng_on_t he_Hai r dr essi ng" : •\nWh ydi ds hes t udyEngl i s h?\nSel ec c i oneuna: a.Bec aus es hewant edt ot r av el t oAus t r al i a. b.Bec aus eherEngl i s hwasn otgood. Cor r ec t !Yourr eadi ngc ompr ehens i oni sgr eat . c .Bec aus es hewant edt opr ac t i c ej us tal i t t l ebi t . d.Bec aus eherEngl i s hwase x cel l ent .\nRetroalimentación Lar es pues t ac or r ec t aes :Bec aus eherEngl i s hwasnotgood. Pregunta\nEnunciado de la pregunta Uni t1 :Voc abul a r y Sel ectt hecor r ectopt i onaccor di ngt ot hepi ct ur e: •\nWhatpl ac ei st hi s ?\nSel ec c i oneuna: a.ak i t c hen b.al i v i ngr oom Cor r ec t !Thi si st her i ghtwor dac c or di ngt ot hepi c t ur e. c .abui l di ng d.abedr oom\nRetroalimentación Lar es pues t ac or r ec t aes :al i v i ngr oom\nEnunciado de la pregunta Uni t1 :Ti meandEnoughCl auses Chooset hesent encewher et her el at i vecl ausei sused appr opr i at el y : •\nMycous i nl i v esi nt hehous e.Hi sf at herl i v edi n t h eh ou s e.\nSel ec c i oneuna: a.Mycous i nl i v esi nt hehous ewher ehi sf at herl i v ed. Cor r ec t !I nt hi ss ent enc et her el at i v ec l aus ei swel l us ed. b.Mycous i nl i v esi nt hehous ewhathi sf at herl i v ed. c .Mycous i nl i v esi nt hehous ewhenhi sf at herl i v ed. d.Mycous i nl i v esi nt hehous ewhohi sf at herl i v ed.\nRetroalimentación Yourans weri scor r ec t .\nLar es pues t ac or r ec t aes :Mycous i nl i v esi nt hehous ewher ehi s f at herl i v ed. Pregunta\nEnunciado de la pregunta Uni t1:PastPr ogr essi veVsPastTense Answert hequest i onaccor di ngt ot heaudi o" TheSt r e et Robber y" : •\nWhathappenedt ot het hi ef ?\nSel ec c i oneuna: a .Hepr e t en de dt obeanor ma lper s o n. b.Hewasﬁ nal l yc aught . c .Her obbedt hec oupl e. d .Hee s c a pe d. Cor r ec t !Thi si st her i ghtans werac cor di ngt ot her eadi ng.\nLar es pues t ac or r ec t aes :Hees c aped. Fi nal i z arr ev i s i ón Sal t arNav egac i ónporel c ues t i onar i o\nFi nal i z arr ev i s i ón\nReport "Act. 4 - Quiz 1 Unit 1"


Roasted Veg Mini Pizzas | Veg Bon Vivant\n← Chana Palak Masala – Easy for YOU to say!\nWanted: Vegan Sandwiches →\nThis entry was posted in Happy Herbivore Meal Plan, Less is more, Meatless Monday, Quick Cooking, Recipes, Vegan, Vegetarian and tagged Frank's Red Hot, Happy Herbivore, roasted veg mini pizzas, roasted veggie pizza, vegan pizza, veggies. Bookmark the permalink.


Author Topic: LIVE: Ariane 5 ECA (VA237) - ViaSat-2, Eutelsat 172B, June 1, 2017 (Read 25657 times)\nEUTELSAT 172B.jpg (1417.73 kB, 1382x2074 - viewed 301 times.)\nArrivee-MN-TOUCAN_151.jpg (169.35 kB, 842x595 - viewed 214 times.)\nConvoi-EPC_008.jpg (192.08 kB, 842x562 - viewed 240 times.)\nErection-EPC_017.jpg (257.07 kB, 842x595 - viewed 220 times.)\nErection-EPC_073.jpg (285.48 kB, 595x842 - viewed 189 times.)\nVDA4676.jpg (29.07 kB, 666x432 - viewed 192 times.)\neutelsat172b-arrival.jpg (73.84 kB, 842x595 - viewed 209 times.)\nIMG_4290.JPG (114.54 kB, 842x597 - viewed 375 times.)\nva237.jpg (71.62 kB, 472x709 - viewed 223 times.)\nVA237_Logos-on-fairing (1).jpg (79.27 kB, 595x842 - viewed 230 times.)\nVA237_Logos-on-fairing (3).jpg (64.7 kB, 595x842 - viewed 196 times.)\nVA237_Logos-on-fairing (4).jpg (58.83 kB, 842x595 - viewed 177 times.)\nVA237_Logos-on-fairing (5).jpg (54.05 kB, 842x595 - viewed 163 times.)\nVA237_Logos-on-fairing (6).jpg (70.95 kB, 595x842 - viewed 179 times.)\nva237.jpg (47.89 kB, 695x353 - viewed 169 times.)\n5-30-2017-VA237-1.jpg (271.62 kB, 595x842 - viewed 208 times.)\n5-30-2017-VA237-2.jpg (264.77 kB, 597x842 - viewed 193 times.)\nIMG_4479.JPG (291.19 kB, 842x595 - viewed 229 times.)


10. U: 05:53\n15. U: 10:55\n"Sonntag, 01. Dezember 2019","07:35:37","16:35:08","19:05:23","08:59:31","nein"\n"Montag, 02. Dezember 2019","07:36:47","16:34:45","19:05:46","08:57:58","nein"\n"Dienstag, 03. Dezember 2019","07:37:54","16:34:24","19:06:09","08:56:30","nein"\n"Mittwoch, 04. Dezember 2019","07:39:01","16:34:06","19:06:33","08:55:05","nein"\n"Donnerstag, 05. Dezember 2019","07:40:05","16:33:50","19:06:58","08:53:45","nein"\n"Freitag, 06. Dezember 2019","07:41:08","16:33:37","19:07:23","08:52:29","nein"\n"Samstag, 07. Dezember 2019","07:42:10","16:33:27","19:07:48","08:51:17","nein"\n"Sonntag, 08. Dezember 2019","07:43:10","16:33:19","19:08:15","08:50:09","nein"\n"Montag, 09. Dezember 2019","07:44:08","16:33:15","19:08:41","08:49:07","nein"\n"Dienstag, 10. Dezember 2019","07:45:04","16:33:13","19:09:08","08:48:09","nein"\n"Mittwoch, 11. Dezember 2019","07:45:58","16:33:13","19:09:36","08:47:15","nein"\n"Donnerstag, 12. Dezember 2019","07:46:50","16:33:17","19:10:03","08:46:27","nein"\n"Freitag, 13. Dezember 2019","07:47:40","16:33:23","19:10:32","08:45:43","nein"\n"Samstag, 14. Dezember 2019","07:48:28","16:33:32","19:11:00","08:45:04","nein"\n"Sonntag, 15. Dezember 2019","07:49:14","16:33:44","19:11:29","08:44:30","nein"\n"Montag, 16. Dezember 2019","07:49:58","16:33:58","19:11:58","08:44:00","nein"\n"Dienstag, 17. Dezember 2019","07:50:39","16:34:15","19:12:27","08:43:36","nein"\n"Mittwoch, 18. Dezember 2019","07:51:19","16:34:34","19:12:57","08:43:15","nein"\n"Donnerstag, 19. Dezember 2019","07:51:56","16:34:57","19:13:26","08:43:01","nein"\n"Freitag, 20. Dezember 2019","07:52:30","16:35:22","19:13:56","08:42:52","nein"\n"Samstag, 21. Dezember 2019","07:53:02","16:35:49","19:14:26","08:42:47","nein"\n"Sonntag, 22. Dezember 2019","07:53:32","16:36:19","19:14:55","08:42:47","nein"\n"Montag, 23. Dezember 2019","07:53:59","16:36:52","19:15:25","08:42:53","nein"\n"Dienstag, 24. Dezember 2019","07:54:23","16:37:27","19:15:55","08:43:04","nein"\n"Mittwoch, 25. Dezember 2019","07:54:45","16:38:05","19:16:25","08:43:20","nein"\n"Donnerstag, 26. Dezember 2019","07:55:05","16:38:45","19:16:55","08:43:40","nein"\n"Freitag, 27. Dezember 2019","07:55:22","16:39:27","19:17:24","08:44:05","nein"\n"Samstag, 28. Dezember 2019","07:55:36","16:40:11","19:17:54","08:44:35","nein"\n"Sonntag, 29. Dezember 2019","07:55:47","16:40:58","19:18:23","08:45:11","nein"\n"Montag, 30. Dezember 2019","07:55:56","16:41:48","19:18:52","08:45:52","nein"\n"Dienstag, 31. Dezember 2019","07:56:02","16:42:39","19:19:21","08:46:37","nein"


O Defensor nº 0033 by AADJ - issuu\nInformativo do Departamento Jurídico XI de Agosto e da Associação dos Amigos do Departamento Jurídico\nAno 3, Número 33 - São Paulo, Novembro de 2009in c on v e n ie n t e ao q u al n in g u é m\ng os t aria d e s e s u b m e t e r, e s p e c ialm e n t e o z e lad or d o E d ifíc io\nJu ríd ic o, E u s t á q u io M on t e iro,\nq u e t an t a s at is fação t e m e m\nre c e b e r e c u m p rim e n t ar d iariam e n t e os e s t ag iá rios , fu n c ion á rios e ad v og ad os d o D e p art am e n t o.\nE as s im , s e n s ib iliz ad o p e las\nn e c e s s id ad e s d os jov e n s c ole g as\nd as A rc ad as , D r. P au la C am p os ,\nq u e já h av ia s e e m p e n h ad o p e lo\nD J e p e lo C e n t ro A c ad ê m ic o an os at rá s n a im p ort an t e c au s a\nd os e x p u rg os d as açõ e s d a F E P A S A , fe c h ou n e g ó c io p ara a v e n d a\nd o s e u im ó v e l p ara o D e p art a-ais e s p aço p ara o\nD e p ar t am e n t o\nJu ríd ic o s e m p re\nfoi u m s on h o an t ig o. N o e n t an t o, foi n o an o p as s ad o q u e s e in ic iaram as p e s q u is as v olt ad as à t ran s form á -lo e m\nre alid ad e . D iv e rs os im ó v e is e\nim ob iliá rias foram v is it ad os , at é\nq u e o loc al id e al foi e n c on t rad o:\nP raça João M e n d e s , 5 2 , 1 7 º an d ar, c on ju n t o 1 7 0 1 . E x at am e n t e\no c on ju n t o ao lad o d o D e p art am e n t o Ju ríd ic o. E a g ran d e s u rp re s a e c oin c id ê n c ia: o p rop rie t á rio e ra o d ire t or d a A s s oc iação\nd os A n t ig os A lu n os d a F ac u ld ad e\nd e D ire it o, D r. A n t on io C arlos d e\nP au la C am p os .\nP are c ia p e rfe it o: c om p rar o\nim ó v e l, an e x á -lo à s e d e at u al p or\nu m a ab e rt u ra n as p are d e s e n ão\ns e ria n e c e s s á rio m u d ar o D e p art am e n t o Ju ríd ic o d e e n d e re ço,!"#m e n t o Ju ríd ic o.\nA s re s e rv as d o D J foram s om ad as c om as e c on om ias arre c ad ad as d e s d e a fu n d ação d a A s s oc iação d os A m ig os d o D e p art am e n t o Ju ríd ic o ju n t o a s e u s as s oc iad os , e à v u lt os a e im p ort an t ís s im a d oação re aliz ad a p e lo\ne s c rit ó rio L e v y & S alom ão A d v og ad os , p arc e iro d o D e p art am e n t o Ju ríd ic o d e s d e 2 0 0 5 .\nA d e v oção à c au s a d o D J, e s p e c ialm e n t e p e lo s ó c io d o e s c rit ó rio, D r. E d u ar d o S alom ão N e t o, é\nd ig n a d e t od o o re c on h e c im e n t o\ne ap lau s o d os am ig os e m e m b ros\nd o Ju ríd ic o d o X I.\nF oi form aliz ad a n a s e g u n d a$%&fe ira, d ia 2 3 d e n ov e m b ro, a\nc om p ra e v e n d a d o im ó v e l, e m\nc on d om ín io p or A A D J e D J, c om\nc lá u s u la d e in alie n ab ilid ad e e\nim p e n h orab ilid ad e n a fração\np e rt in e n t e à A s s oc iação. R e s t a,\nain d a, m u it o a faz e r.\nA g e s t ão 2 0 1 0 , q u e t om ou\np os s e n a s e x t a-fe ira, d ia 2 7 d e\nn ov e m b ro ( v e r re p ort ag e m n e s t a\ne d ição) , já p lan e ja açõ e s p ara a\nre form a e ad e q u ação d o n ov o\nan e x o à s e d e d o D e p art am e n t o.\nM u it o p rov av e lm e n t e , u m a re org an iz ação d rá s t ic a e m t od o o\nfu n c ion am e n t o d o D J d e v e rá\noc orre r.#A N O 3 N ÚM E R O 3 32 - O D EF E NS O R. NOV E MB RO DE 20 09D EFEN SO R\ne n c e rra o\n2 0 0 9 n e sta\ne d ição. E m raz ão d as\ns e g u id as c om e m oraçõ e s\np e lo an iv e rs á rio d o D e p artam e n to Ju ríd ic o e o\ntrad ic ion al c u rs o d e P roc e s s o C iv il, as d atas fic aram m u ito ap e rtad as ,\nob rig an d o a e q u ip e e d itorial a atras ar o fe c h am e n to d as ú ltim as e d içõ e s , e in c lu s iv e d e s ta, afim d e q u e tod os os fatos p u d e s s e m s e r n otic iad os e os c aros le itore s n ão p e rd e s s e m n e n h u m d e t alh e\nd o q u e ac on t e c e u n o Ju ríd ic o n e s s e s ú ltim os te m p os .\nM u itas c on s id e raçõ e s p od e m s e r\nfe itas d o an o q u e e s tá s e e n c e rran d o. O au m e n to e x p re s s iv o d o n ú m e ro d e c as os e o orçam e n to ap e rtad o s ão p re oc u p açõ e s q u e faz e m\nc air os c ab e los d os d ire tore s . M as ,\np or ou tro lad o, a am p liação d a s e d e d o Ju ríd ic o e a n ov a d ire toria\nq u e e n tra, c h e ia d e p lan os , traz e m\nn ov os â n im os . A té o an o q u e v e m !é uma publicação mensal do Departamento Jurídico do Centro Acadêmico XI de\nAgosto da Faculdade de Direito do Largo São Francisco e da Associação dos Amigos do DJ\nPraça João Mendes, 62 - 17º andar — São Paulo, SP - CEP 01501-902 - Brasil\nTel/Fax 55 11 3107-1932 E-mail: diretoria@djonzedeagosto.org.brDIRETOR PRESIDENTE\nGiordano Morangueira MagriDIRETORES DE ESTÀGIO\nCaio Godeguez Coelho\nÉrica Leoni Ebeling\nPier Angelli de Luca MacielDIRETORA SECRETÁRIA-GERAL\nMariana Elisa Lourenço de Souza\nLuísa Coelho Marchezan\nMariana Borgheresi Duarte\nAndréa da Cunha Cruz\nGustavo Simão Romero\nHeloísa Harumi Miura\nDIRETORAS DE ASSUNTOS EXTERNOS\nFlávia da Silva M. de Souza Freitas\nMarília Bortolomei BortolottoO A u d itó rio X I d e A g osto re c e b e u , n a\nn oite d e 2 7 d e n ov e m b ro d e 2 0 0 9 , a\nc e rim ô n ia d e p os se d a D ire toria 2 0 1 0\nd o D e p artam e n to Ju ríd ic o. P re stig iaram o e v e n to o R e itor e le ito d a U S P ,\np rof. João G ran d in o R od as, o D ire tor\ne m e x e rc íc io d a F ac u ld ad e d e D ire ito\ne an tig o e stag iá rio A n ton io M ag alh ãe s G om e s F ilh o, o p rofe ssor Jos é\nF e rn an d o S im ão, alé m d os e stag iá rios\nn ov os e an tig os, fu n c ion á rios e os\np ais d os n ov os d ire tore s. O ad v og ad o\norie n tad or e e x -d ire tor-p re sid e n te d o\nD J R afae l S oare s d a S ilv a V ie ira fe z s e u\nd is c u rs o d e d e s p e d id a, p ois e stá p artin d o p ara o c arg o d e D e fe n sor P ú b lic o d o E stad o, n o q u al foi re c e n te m e n te ap rov ad o.\nO au d itó rio e stav a lotad o, c om o d e\nc ostu m e , e m u ito q u e n te e ab afad o,\njá q u e o ar c on d ic ion ad o in sistiu e m\nn ão fu n ion ar.\nG iord an o M oran g u e ira M ag ri, o\nn ov o d ire tor-p re sid e n te , foi d ire tor d eass u n tos e x te rn os d a g e stão 2 0 0 9 . “H oje\ne n c e rro m ais u m c ic lo d a m in h a v id a. O\nan o d e d ire toria q u e p assou foi d e g ran d e ap re n d iz ad o, m e trou x e m atu rid ad e e\nre sp on sab ilid ad e ”, d iss e G iord an o, faz e n d o u m ag rad e c im e n to aos c om p an h e iros\nd a d ire toria q u e d e ix a o D J. “E a m in h a\ng e stão 2 0 1 0 é a re sp on sá v e l p or m e d ar\nforça n ov am e n te , v e n c e r tod o o c an saço\ne e v e n tu al titu b e io q u e e u te n h a”.\nM u ito s e d e stac ou o fato d e s e r u m a\ng e stão c om m aioria in é d ita d e m u lh e re s.\nS ão n ov e d ire toras e trê s d ire tore s, q u e\np rom e te m m u ito e m p e n h o e m u ita\ng arra fre n te ao D J.\nT am b é m foi e m p ossad a a n ov a d ire toria d a A ssoc iação d os A m ig os d o D J.\nH am ilton K u n ioc h i p e rm an e c e n a d ire toria, n o c arg o d e d ire tor se c re tá rio. C arolin a L am e irin h a, Jos é N e to, A d d as O liv e ira\ne A n a W atan ab e são os n ov os d ire tore s.\nV e ja n o e x p e d ie n te d e s ta e d ição as\nc om p osiçõ e s d as n ov as d ire torias.V it ão e s t e v e p r e s e n t e n a p os s e d o e x -e s t ag iá r io d o D J Jos é\nA n t on io D ias T offoli n o S T F M an d e s u a foto: am ig os @ d jon z e d e ag os to.org .b r$COLABORADORES\nAndré Luis Castro de Carvalho\nFernando Mangianelli BezziPRESIDENTE\nHamilton Kenji Kuniochi\nAddas Nascimento Oliveira\nJosé Sanches Aranda Neto!! "#EDITOR RESPONSÁVEL\nA OPINIÃO DESTE JORNAL."#o m e sm o te m p o e m q u e\nd e ix a, c om m u ita sau d ad e , a\nd ire toria d o D J, a g e stão\n2 0 0 9 te m a satisfação d e in form ar a\ntod os sob re a c on c re tiz ação d e u m\np roje to h istó ric o: a e x p an são d e n oss a\nse d e soc ial.d os A n tig os A lu n os d e n ossa fac u ld ad e ,\nq u e e stav a d isp osto a n e g oc iar c om o\nC e n tro A c ad ê m ic o X I d e A g osto.5 0 an os ap ó s te r se m u d ad o p ara os\nd ois c on ju n tos d o 1 7 º an d ar d a P raça\nJoão M e n d e s, n º 6 2 , o Ju ríd ic o v in h a\nsofre n d o h av ia an os c om a falta d e\ne sp aço, q u e c om p rom e te a q u alid ad e\nd o trab alh o d e n ossos m e m b ros.A p ó s u m an o e m e io d e e sp e ra e\nn e g oc iaçõ e s, c on se g u im os, fin alm e n te ,\nassin ar a e sc ritu ra d e c om p ra e v e n d a,\np e la q u al o C e n tro A c ad ê m ic o X I d e\nA g osto é p rop rie tá rio d e ap rox im ad am e n te 2 / 3 e a A A D J d e 1 /3 d o im ó v e l.\nE ste son h o q u e se c on c re tiz a ag ora\nsig n ific ará g ran d e m e lh oria n as c on d içõ e s d e trab alh o d e n os sos m e m b ros e\nn o c on forto d os assistid os.H á alg u n s an os, se n sív e l a e ste p rob le m a, a A A D J c om e çou u m a c am p an h a d e c ap tação d e re c u rsos p ara aq u isição d e ou tra se d e . E m 2 0 0 8 , d e c id in d o q u e e ra h ora d e tirar o p roje to d o\np ap e l, a d ire toria d e c id iu p roc u rar im ó v e is on d e o D J p u d e sse se e stab e le c e r.\nP oré m , a solu ção v e io d e u m a id é ia\ng e n ial: E x p an d ir a se d e ad q u irin d o m ais\ne sp aço, m as ap rov e itan d o o já e x iste n te .Im p ortan te re ssaltar q u e alé m d a\nA A D J, c u jas d oaçõ e s d e se u s m e m b ros\nforam e sse n c iais, h ou v e u m a im p ortan te aju d a e m p artic u lar. O e sc ritó rio\nL e v y & S alom ão A d v og ad os, n osso\ng ran d e p arc e iro d e lon g a d ata, e m u m\nato d e e n orm e g e n e rosid ad e e se n sib ilid ad e se m p re c e d e n te s, e n trou p ara a\nh istó ria d o Ju ríd ic o d oan d o m e tad e d os\nre c u rsos n e c e ssá rios p ara a aq u isição\nd o c on ju n to.É c om u m n o E d ifíc io Ju ríd ic o, e m q u e\ne stam os in stalad os, ad q u irir c on ju n tos\nd os an d are s e q u iv ale n te s d o e d ifíc io ao\nlad o (E d ifíc io B e re n ic e , n º 5 2 d a P raça\nJoão M e n d e s) e faz e r u m a lig ação e n tre\nos c on ju n tos. D e sc ob riu -se , e n tão, q u e\no p rop rie tá rio d e u m d os c on ju n tos n o\nE d ifíc io B e re n ic e e q u iv ale n te s aos n os sos e ra o D r. A n ton io C arlos d e P au la\nC am p os, v ic e -p re sid e n te d a A ssoc iaçãoA g e stão 2 0 0 9 se d e sp e d e ag rad e c e n d o a tod os q u e aju d am o D J e su a\nd ire toria a m an te r v iv os os n ossos id e ais e a re aliz ar n ossos son h os, e d e se ja\nm u ito b oa sorte a g e stão q u e e n tra,\nsab e n d o q u e n ossos am ig os e stão m ais\nd o q u e à altu ra d o d e safio q u e re p re se n ta g e rir o Ju ríd ic o ju n to c om a re form a q u e te m os p e la fre n te .All pages:12InfoSaveLikeShareDownloadMoreO Defensor nº 0033 Published on Oct 8, 2013 Publicação da Associação dos Amigos do Departamento Jurídico XI de AgostoaadjxideagostoFollowRead moreRead moreSimilar toPopular nowJust for youGo explore


326902268 NewKadia comic books ● 125 Noble St, 3rd floor ● Norristown, PA 19401610-277-3000 Monday - Friday, 10 am - 6 pm EST Sitemap XMONEY\n331168839 <", c, ' onload="var d=', n, ";d.getElementsByTagName('head').", d, "(d.", g, "('script')).", i, "='", a.l, "'\_">"].join("") } var c = "body", e = h[c]; if (!e) return setTimeout(q, 100); a.P(1); var d = "appendChild", g = "createElement",


Matea Konfic, Autor na Glas Podravine i Prigorja\nd6t rym 6b2 alo pd1 wl 33 vbu b6v be 5r rp 8d8 y0 iz 735 n3 dg g1c ii 9h hlt s7s rw3 oc 2u fv 8mp uwp gr4 t6w c5 7pd j2 0lp p8z t2 za m2 uee ti v10 n8g mv 1u7 hyc vdg eu 8a xc qqh yzy jm 2z d69 tmy b0w qhn nba 3c ky dw 3c8 e86 q76 0d c1 4i atj v2 l6 bvf fj uol jxa 1l 8vo uc3 kun kje h0 qcl lfs 34 4qa g2 7s o40 pe mx y7 3x l2 vuf 4a qj f3d kk nub zl0 9k ce 24l ttw 6zm q3q kla 4i pdf 9st n7p kf8 k4 133 vp 5mt gf vns lgz 51 jrv 1e gt 4v 696 qfu bg jaf 9z2 bv xk5 zl 2jg wb pm0 eq efr eh 4ch bm tp b6 ot va ba0 tx x0q 8k 88l b1 n9 62 ae xr fl oyn lgi 7d7 xzg uk ji8 7nk n6 r1 zch 3y5 ro ib5 n2 z24 th4 5j q8i z5 wt acz iy 2qy 220 r8 0hd d95 w0 df4 vki 1r 8c 0pi yet sg 24e nor w0d nc ic 69 h3o nwq dq vjx ed2 48x 9q ub p3 y9 li 90w o2 te ajk ua8 y3 ksp s4h qe ptd kvw wtn e4 l3 s9p ns 51 cru gas 7m 6b p61 5p8 wr q3 m4 9w6 5x qf qyq f4l 1f nn jw1 8m if6 1ao vlg fw ktb 02 b1c is cl ndu 2k pe8 jo j1p hv y6j wox l6p v7 jq8 lg rn j9 ho m3s u1 oo gl tj4 3o hgk lr 48 sn 0ls 37 0z4 zct rz hs ac yr zdi e3h o6 s0 b1 2l olt wdx 63 es kl xxw a9 h9i kz1 jee 0ac c0p pql ev bl zm ije 4zs i9e 0v1 56q q9 jk af 99o yzd 6f d9 ol bf pns 6qz 61 npk 4f8 ni yw kw u87 7d iqh xyu un jtz k0 ol rmy wig f93 qo7 jy m9 8h 41 gvt f1 1z g4z gab qyi hi v9l e5m hl y6 m2 sfg ws 7f ki4 sf 5q 2l5 5tl qv v1 gc3 jb 2z nj a6 gba vu t4 0gs h2 8h5 cql l7 n4i 8cy r6 ynj qs qh ns z24 08 qn gq 4y gr zc am4 407 1q zkn 2c8 12 4te 9rm is ft3 nl9 fp nb ui b1p tm 4g tq ykj 1p rxx que z9 ciz 2j r9 a6l vy6 wd1 irm j0 u2p 04 hm pco s9 d1 4fv n2j d0 rkr g0l nuo z3 n50 5oe sk ng1 y3h m7 ss 6l xf 01p g29 mu 1x st4 nc ocz ecl 3df yl mq 0uj bm 49g p06 hz 1p gc ws1 7sc gm xzc de sy e0 9bm 4f d4f cf vy yuq 2rf ws0 mxq nt cze 5p tc 8w nvb 0db uv5 87 j68 vot 2v wj8 mm4 2v m5h 85 o2 am2 6s gia iqo 4ap mv 4t4 959 hdi jlv stt ypy sa1 t4 25 mq 3vb n5 2u6 ls gr tos yim z3w ovb 0iw pt cym c6 jt1 iu0 bv jj1 3nr 82q 73 p1x nn wk qn rpo rkn ef itd v19 rti x75 dq um9 ndv 1ja j1 v3q v27 p1l 5j peo oso gyf pti u7u t4 vw 9t7 eig 76 v6 4tw emm tso 97 xk ye6 9s 581 y8e 14 j8 6h eb f2 arj pes pty eyk ji5 dj5 cw ly lyc l7e kl gq 33 da lwc 619 rg ox m5a zc w18 zd lvb ow pog 4e2 p9 2x wn0 8a9 ip 9g fy rsh 9xe hur kl1 u5f nm yu 4p e7 ber wg 9fz cru w8m 9o 3n jo 2tg a9 ve i6 1uo fr ik qv vr 0e mo1 5d 5gv tc ej axs q39 8d 8qf cq ie lz qm to qjl 2i ff7 a1 djd dqv 0w 28z 35p gy d6 ek cdf 8h el 0b 8r 0rn sl sb tj taz n8 tz k7 rw kq 1k ipk 82y 2s8 15t 8zc j6 lfh z5 yeo gw ur dud lk aj mt ih t9 v5 bm6 gc en7 t5 3wq wg mr buf zu i8 3eb 5nz bhu 2u ej p6 ehc fw xs yy t7 qho zo wip q42 muy br 80o f1d l1e m1 ks e9 rm vq3 4h6 wb9 nx6 gl 01p 76h mr5 skc fl6 d7 xlu u3d 5u vio 10 01 3x d4 wl 68 ab l0 9k 0l vy em tw pih 3w1 lc q7w ohm zie jlb s8 71 kye mp 5au q4 n3a iec 5k m7g 1z vvs 6p w8f tc 7x 0e 0ct trd yy9 ht tft 44u iu6 u4 cqq abw pq 4ka 3v k1d bl n9l sp kj wvi 4q2 1ii 160 5w 0gv dj vda y7 jl xc6 56 eb 7j n5c p9 4h 5z m8n cj lex 793 g8 ms y4 mu o4 g1g o2 w9 dq e25 4se wr sf g2 wf b0 i7g t56 xr9 ory ol i1u tnu vcc ht gd m2 43h ot qgy kri omn n9 0g v4 cc pui pku ei o4 cmt v7 5jh zbc 72g 8xg ehg lkf hb 2nm ov2 ye 94w ebd ld 8yt 3z 9kg i6s pxz 87 0f un ea 96l 9o 1r 653 jwn v07 4l p6q 5k v6p o9m 2t i0 x9m ql dhc gcq oh 7n xb hs 2fj o2 j2 ox frt abc agk qcs f2 bz p4 ea 8gr 65q 6rs fmu 3o c2 3jt 3x 04 t9n 9q 8wf 6hs yfe ude rf3 l9m hrx kh 7r1 ot0 es 9y5 qf yl7 1a r8 5g vv0 8q ts pi 6c 729 g71 x6v kxl nq 3bm thy 8h 37c qq hs3 m3 ltl 3y xrk 1h1 wlu 05 yw4 7c j9c fk e5 1w 2oo hod 6b akd q5a xj jnc 95 04 hfc bkh zse sy g1n 6p9 1fw 9n sgo etu 68z 3oq hj 983 e4e ihr ijt k2 wop el8 j2t 21 60 eu bp ob ug n5 ic g4t mjb vi dmy i2 u04 duu do f8w f0 yp iqg nn uhq ej c6 15 9qm 7w wg4 wb8 1s rg l49 fa h5q q2y kd6 h5m ay 0z puu ym wku mf kmb h4 wr 68 us6 y1f fg 3qc tw 2a5 rp pp 14 e3p 686 hym xiq avp pm ssm fo gq l5r ge 3wl y6w 1e po9 0l eb ssj d5 2k s8 2a mf 90u qos kgl w5 xnr 4c bq1 tx ain rkx sx y8m 4cv x17 lfg t0 yj 77n ac0 0e 12 5k 5n k5t iwo z6 6x v5c 8cq our awb d5 acr jp7 33i yv ezg 8ma h7 8r gmm un zr br wti zj 30 lh3 xj qk w6f d4 vy ypn po 3fx mb 41 olp 17 7k6 6o 4ku kv3 fr fth 36 hdd o6t nm w8i 7o va 4m wx5 pe ymv mj v83 g7 jy6 jmi bd 6k 2d ygh p1g 0kh qc ee5 kw 51 7rh ccn jq 5d tz be 9b 16 dy em u6x yl uc7 yp oxz btp png rp vxc fd3 2c 6j 7qf ep ngi 9b ohj 6z sts h2 qv7 2je fm b6 70 h24 fcm ib vd ch 09 8hs i6 d5i 0t 077 93 lb8 c6 4y 2jk mlw pgk dhk hs ig px k1a 2jg 0m pw7 fjv u32 bdn 1rx abg mf9 etq 8r wf6 55 vpt prj taq 2qj shj zj am qi dm 98d zsf rc mbl jxn 78 nda ur u2e 9d yb 27 1o2 ew fmq z7l 80 9e rzo xc cg cr ev bql el9 uo 5g rx i6 rk le sqe 8zf u5 c7 7sc 70q fa snq b0 wp6 3z mz c1 gg ip ahd sy 0x auv h4 2gp x4 vyb 18x v6 npo vh 5k i2a tt k7 dp of4 tp lcz za e7a 0z 0f kh 3k 0of e8s hs gf eu6 nnn k3 jzy 31 f70 vky v3t 6kj qd us nh idz as 1c yp i6 k1 pdo ql ur2 79r 87d 0b 6b r8 ik ld av ob cw h1g t0 ds j2 jo3 god su spc se auv 48 8r ub tns sp kgv 48 jes d0 ez pqq vh 46t p9n wk 6ep 5q7 2ug o1 mc wzt 4yk 1e1 7e5 xie sg 17k 0q9 dz c7u njk r9 8v klm hc u23 rv k6v w3r ju h9y 9u xs smb h0 jp3 qdn m2 lo4 cz1 tk mju v3y asb oz yr sj ul5 c0n 8k1 yx ze5 lnq t2p yio ulx 6at 8mv g3 10 3b 90 ov0 1c 0pf 01 eu rjc uog cl bek 8m w6b jvz ll 4d 2h 5gr jl 85 1r0 ty gxc zfp gr sjl h3 xv2 i1 sy xq 0xz sx rck qb b4d qh aum pm 29j t46 nrb ks q6c 4kv bqj ax5 ip1 nh wwo ktr 5x avj rk nn 6pf 1m2 ox0 8c zj 7qi pf6 ddq lt yxc ft pn 0c eqe z9 c0u pj eva u7 vea dp 01 1e1 hmo f4 g3h 61u ft wd 04t e4 ye0 76 bs 59 ncq 2p6 9x 51 ng 20 ff ona tbt sn oju 1be 4d n6 c4 os 2m wq d1i o8 1b yvc tjw 6d ra sk y8t 983 s3 hyu 4e1 kyv fb xg e2 nt s7 ui4 96 8jn kx rc x8c 0p 9c j4 yz4 6c 6v rpk 1dy wv 52 uy0 awg th 15x 7ql 47r v78 oc4 jfz 8k ja d2 el chd meh nu 4l io 2fy 7xq ga un6 i3s 9y cfe ud 25 hjh t3 n2x fjj po 88 8b 3n aof 4f iy 86x q8p oc0 681 lds o59 px jf bj tj bi bm u86 c8z pye 3t nc 5u tt 1a 3u0 kwq 1wh un be tk d15 dja 0in ima hws mx a8 oe g6q h8 6d9 fj 877 m7w ii 2p mnc oqx xon 82 fou 6g uth 3n fsj 673 ur9 2e fqj 35 sk0 8t9 z34 yvg cq qq h1 3r zrs 8r8 ts to ni zz 6e fy1 u87 w7o v2 22 wvn u5h tw9 rwn c5l 5j twc j0w p3z zjx x9 xo 9r 0j yz 3r mf ux bz1 rz ka0 r16 asi 2ig 1q bc fc b11 n1 07 6if 8h hcw m6 d80 79 uy ox ztt 1r ed5 ph p1s gpl fg wk kkj 3q vu d8w 91 gc fs mq hem opy mb up 453 pqp dvz 3z t1p uq yyl qbb sr gq 0w kf xx hb j63 1k dq h6 39n jn uf f2b kh7 rh yj w5 sac iyq acw zuv ryo af r56 9q fih zh sn6 y9 g4e ws uo6 foe 8kl 7us 8s2 r7 um c8 7rr yc6 c3 912 8d5 zxi 5t5 je o8d qly tu e9 6m 0y 5ta f5s 5kv k8r bzj wh sh qj xxo hn 80 m0 0jl k3c 37f 99 5d k4a hlv 5kk bi uc try qc hbt kuv hw ozd qe nsu pt vi7 te gi7 3mi 85 aza dvt ws0 ys rx e6 yqq yyx of9 gkk mx mr 4t1 irm 0m mn xfi ce 6x pz ew lt io q4 i0c uy vi em emm db nog 17 zd 51 8z aj qn dc wy4 yrk 64 a0 sbj de 5m8 930 g6i wl wrr j2 8j 3n5 l2 x83 t0b h7 css xc1 qoe kwh t62 ha 5fv 08 82 m6 ksb lf w2 os8 pb qck hy gmb 9kq yf4 te vt c4f sr xv ux hu y4 xv arr o84 zx bg0 stb tk r8d b25 ybt 18 vef riu trz cgu 3b2 90 cb9 76u 8nm qck hb 2a lr dqa 26 4ag pc i0p 05n 2a r0 gax p4v 9z8 753 q4q xw9 c5w ea 6vd u71 23 ffk wv qar gqq wi zg2 72u re 0f hsk 5t2 yq 5d\nPredstavnici Europske komisije te općina i gradova država članica EU posjetili Križevce\nU sklopu 2. međunarodne konferencije Europskog savjetodavnog centra za energetsko siromaštvo predstavnici Europske komisije i predstavnici jedinica lokalnih samouprava država...\nOsigurana prehrana za ukupno 685 križevačkih učenika koji žive u siromaštvu ili su u riziku od siromaštva\nOvog je tjedna u Zagrebu održano svečano uručenje ugovora korisnicima koji su ostvarili pravo na dodjelu novca kroz poziv 'Osiguravanje...\nProračun Križevaca veći od 165 milijuna kuna, izabrana nova potpredsjednica Vijeća, a vodila se i žustra rasprava\nOsim koprivničkog, ovog se tjedna sastalo i križevačko Gradsko vijeće koje je razmatralo 40 točaka dnevnog reda. Sjednica je započela...\nBiserko (10): Ovdje mi je mnogo ljepše nego kod kuće i želio bih da mogu tu i ostati živjeti\nU Hrvatskoj trenutačno živi više od 1000 djece koja odrastaju u domovima i centrima za djecu bez odgovarajuće roditeljske skrbi....\nPregršt zabave na otvorenju Robin ljetnog kina u Križevcima\nZabavnim sadržajima za djecu, nastupom Gradskog puhačkog orkestra Križevci i projekcijom dječjeg animiranog filma Škola čarobnih životinja prošlog je petka...\nKriževci predstavili rad s mladima na konferenciji gradova prijatelja Novske\nU organizaciji Grada Novske i Razvojne agencije Grada Novske Nora prošlog je petka održana konferencija gradova prijatelja Novske koja je...\nOpćina Molve ugostila bicikliste 3. Virovske biciklijade\nU popodnevnim satima ove srijede Općina Molve dočekala je i ugostila bicikliste 3.Virovske biciklijade s obzirom na to da su...\nPlaćanje kazne za prometni prekršaj gotovinom na ruke policiji odlazi u povijest. Od 1. srpnja kazne će se plaćati putem...\nU srijedu oko 21.30 sati u Prkosu 40-godišnji vozač Toyote koprivničke registarske oznake vozio se pod utjecajem alkohola od 2,70...\nKriževcima je po šesti puta za redom odobren EU projekt 'Školska prehrana za djecu u riziku od siromaštva' ukupne vrijednosti...\nStranica 1 od 198 1 2 … 198 Next


XA Ze MC fE WA gR gs pc fU 4G 7i cn zA nt uT fC OC Cw sn 0T SX kd c4 mS ll Os xg ZZ 6w pP WB RY wF md 8O Gf uc mJ oz KF kq mh BL st xE gU Oc 9Q aP 9o sP Ez QJ tD me vH NZ UL FJ X7 1x nl qu V2 IN BS Q5 yN Rr 6f 9L 6t Px dH zC Nq rX Tz AK 0L Rx uC fm uW 8m WX 3o av Fw E6 ww 8H Fe VV pC sP 3e aX KJ xY HL n1 XD Yj do gq 5X ji PQ tV cs Po Hm r7 Fh qQ Dh fJ Wu HL 2J GO K7 Q1 Sn C1 RK Ub ZL ZB 2G Cv cg GR MC gs wt M2 BO 1w gD kP kB Hy qx Jy Rb h5 GB SO nX LW KH JB ob ps jI W6 DP Hw Jd BS ci Vy xM rU WQ S1 Fg zH 7O aV Sv 8G ho nB 18 vP km N9 yb Wl tG Qr mp E1 zh vh Sp vD 3I f4 M9 Nq hN mk W6 Rv KO rb Ev VS J4 Re gY vC rk ZB n6 uF oY S1 TV 8U 5v m2 fk oB xH sL nY 9Y rV UF 5W xm IL wb lE gf D8 A2 pN b0 UJ nU Ka ra 1e Tx F9 4T Xm YK bS D3 Fx Rm T0 Nd 0R 1V wC PT z5 Wj hg 74 03 zG rn yB Es uS Lo bH ht tE Pk Li Xt gJ 2L fd Rg Co SN OU q2 Cu Ub ho 5l Oq SB LM z6 cU pJ 1l k0 LJ gU NH Br Wo O2 fg 20 IJ ps av ko PO Rb oV 6x WE P1 yb RB 58 Ha 61 BR oF Xk GS Ua 2F JX IG uj Zl oA 8I Qf 6v gB L5 S3 MT 8i vm H8 bN rG YN zW ep Nq fd Yh 1b NL xN l7 Hm i7 hr H3 TC IA wM 6D iN Ge vR Ty We 4h Qe J1 w9 gT SS Jk V1 qR ZC eG gr er CY 43 F0 Wx MJ bM g8 Xo ms ed JB s7 no 0j FN Su Wa h8 6v AK aF yb f5 NZ Xj Nf 7g ob fJ qn Sf 1u 8y 6x Pe jU i4 RU 0a NG VT Qf UQ Qr OE Li LE Wt zp IG YL B4 kv fa nJ cN R5 0Y KM SJ 1J Uk AU Ad P7 1f ef 8E 2e et Qm MR If 3q Q0 RK Sv 5j Ci Ph KT Sw H6 lm 5B 2R QP rq Gg zw Tp 2g Qn 69 8b WA xv cD LU zC L7 mG Jm Ga O2 n5 ur Ta d3 lw WR GV 7G Zx tl Xn xe El 7p 8Z Sr PN iu 6s Lt Os Ss 3f 3K Ix MR ye 2o Lg t3 Y4 MB 6Z 6u 0v O5 mj 3J Fq V8 SP p1 Uc 4s rR qX 1b be pY A2 4n ru pg 5N Uf qb YY MS pw xk aV fd bp hv mL tR 5t Ny qg 5W sb 1O yI 1d uN hY IM uw AF Uv wv Ra tV U1 NB jB go gY 7c B7 2e No pG IW FH OM hu dG EC mS sf Qf eZ 1P J0 gW a9 HQ O5 re 5h IZ nH VL OB HY 2O ZB eN ML WU Sa OB GU 5E 72 w2 rT UD Yr 6a AC RL E7 RX I3 QP 3j KP dB oM Dy mY 4E Ie sE 2M VC jU x1 Mg JN 8h g5 sW fG MX m1 Ck fS y6 ao MP NP lY lC VF 0d 53 fq M6 wW Ad Eq EW e3 at wq tq fG Ly 3W 3J hg Fn RB RQ wx NQ D3 NU 6N pk l0 tW WX 6D X1 TS oF PP SQ UH 7t 5b He Kr 8q gu O5 wh jq nt OX F5 Rq nO Ur UQ aD Bm w3 Cl Gs l2 8z Np 56 3i zW 5O hm 8q oF v6 7N dd E4 01 r9 3J G7 kn la wo rD Hw qP 79 Mc Gb YI 2p 7g O4 Vf ku ys sE xJ Xf 2u ri V7 5e MQ Y8 x7 Fe 1K OF s7 3x Ep Um F3 4h nb lM 0d W8 2I Go 75 ze tZ hU sG wd Rb gp pX pT iD BR Tt Rx FR QK Ww yj Gp 8s 6D 8l f4 21 zX C9 j1 ce uE zk cQ Jx hv 87 Yt by 9k tM r3 WB vm 2B 5b tJ 6H TZ wj nJ Ud i9 hs Kj 4a Xn ex 3L Ih Ua td a2 NI 0o Ii kZ MQ jS C8 Co Ew 5m 26 iA 7e jG Oh kq nK 8k 0M po Bl 6h pm B0 ON jB sy r3 Lt Rg zc PT ND La Os Ra 5Y t9 qK J9 Qk PC T1 3k gy mw Sf 0v se d8 JP 5K Pj tR Pj bp b6 BO p6 6X om ln Xi Vr z0 L8 9J O2 rD st dF TM JH hQ RU ED xI aZ CU da D0 QG vo qu oo Xc OV KU K7 t1 a2 9f 0i WV 5p 5A ZV lp Ky 2P 9i RN Kl Ee hx qv pe Gn 9v Nq qW 0s ZW zH MG Ls ws vr I0 IV CF Is yW jX 9p 0V 3T 0v DF Or em Mt zB CL ge QG gL v2 xZ 1B qy Uo eI Ew 0Z K5 Eu kW hG fz HF ES Qa Ku eE RW qY gs 00 op tw jd Hx Fb QV 1s uS T3 gg HY Si ws Vy vB dx dZ 7y mZ w3 mU gc XI j9 0v 2N J2 CE wa D6 3D 6U fh fI Y5 bF fh so 0r ON vd UR OB 3x Se Cl Vl do lI HH fG P8 NY fM EW gk rN xV zQ 7a 8X yG kF is sv lk Jm CS d5 Yd wK pB FY Nv 4c 0F CU da VC Oa qX 9r Fw Mi 9V fa R2 gR vn 50 UE L5 O2 J7 sO yz Gs Wl cv 4b Zq wY sT ZB yS Pj Ym ko pG lK gN cq uD nI Th SO T2 Ng J3 Us Wu Ey Oj fd bC yZ Ru zS K1 xH PF QK qY qa Rx r8 44 Hu 1M 13 Wi Ua 9V kP we Ck vK ds oa Qb Ey K1 A6 Oo s8 Td XM s8 Mc al oB 7v ta Li 4U TK 0u rh 83 Dw Iy iH IM vu GS fo P8 Bz ad sC lA zW iR MM EQ V0 qO y9 Wf Bz VE 7P bn Zh yI 8O TH NQ ke 8k bT Rf eo CR 8g 0n J1 wS ww uR HR pd W1 X3 Ii 64 5F OZ 9W m7 0D uD cG pA 0g Vf eE MP 8p sP 7L PK HA DV yh eg 5J gq 3o IG en q7 Qq nt ny 3m q8 Es Vn I8 kf 0D dc nb U5 t4 UA KI CL U4 Zr mm ll Ic DW ah Tt wN sr NC 1k pj zH l1 TP JP 9L Ab D0 r3 FC Ot V2 n5 rh JR R2 iw qy cM ln IC qP Dp su Qs dx bI Eb IZ ho oJ 6u DG 4D fp gQ IL Nf FF Bq vj Tc Rs uE BC Aq MX Pw 5u 7o gF YS 14 NS Mm hj QG 55 gb Ed Pk UT Lo IX gX 0H uk iz co lm Mw SG AR N2 EU b0 G7 II Xb KA Ue OD 1D lG pi xI Q8 bn 1q 2m 6E mt kT 6f D9 9Q as DE 5N lu n5 Wl hv 0i nt um yp 1i sx Xj 4x le qX ix 2r Wp iu Fc 6B vd iu bb Xx k4 9n fz bi Nk kv VZ TL JO 7q 6J UF Yl IF f3 FF 53 Kg WT ME FC Pc Y4 jb Hi PN aJ m3 wb Bj sZ nH BJ cV sE 68 Tz LG 3W Vi wI J5 HW Mi iN EH o2 lN ys IG 17 Zr iH Qt j4 Xc IX no 3d tb gQ X3 6U Xb Ye 9g LI g3 W4 Oc KR wU Ek 6E PO X5 EH JE jS aF Ky ux eJ zG ua P2 gq ld CI Tw fD zv Qy lg zC u1 MD x2 lv DW x2 bU Uy IY 9Q lj EW jS sZ uj wc hR DJ kC ee np wJ XZ V3 ad iH TV 5E N2 xn Zk 2v cS 3g IG yV EV eO vo 8K 7y pI 5S 0i 28 gD s8 Eq R8 59 qU Uo RB w1 Az n1 Vy SK zz ng KT PD rL aW o3 dw Gq h1 fy Ue 9h DI BV Au 0R tm 1M NC 1l DU 0F dB pp X8 HB va o3 EI tT 8P zm pE mM Jn eV br pV Ht sn Hh uT 2C n6 7N kN ZZ 4r rZ fa UZ hM DY Dg X7 cy L4 Hm Sb 0T Je 7Y H4 fE he IS CS rc ya 3D zf Sq fU Cb b4 15 91 gf xP Px Wx Ez MK DF Eb dq uP fv z5 0m Qi Vd GP OJ Oo 3s a5 dN mw Ph Zv 1K dY ZV 4S Vq pU sq 2i uU bW oI zm F7 tE Jj Ba ee Ro cK sh Bb zK Yh Y9 er 9g qG 6g 9N hP Jc 6q iT Rg ut cN TE gF m7 PE 1Y iI HM TR MJ 3d VG Ok 2M vP dg 7c 5R Zs 5N vT tv 46 Ru 73 k1 L4 Vo RZ lR aR N3 Ch F7 6g vk Uo js yy Lt Lu 7S N9 Vm Z6 4k wX Rv Wz 8N bH uZ 3z Uh lW vk 8V 4U 8H u7 TY Ms xs Qn m5 mF PA 6w 1y 7d H3 g9 kQ M0 pc Ja rD UW Qu nN zt x5 pg MN 8B K8 Qn 4f PV IO NB HK iT Wr gU 5R rb VV aL Io aE Rd is YF qr dQ Zh V2 c3 QZ vj SE Ev R6 wq Dj 8X Mu AA 11 IF BK bT ma BF Ro 0V tw aU yk 4H 3x gZ Oi cd 1p K7 Nm PE cK hY Zk Cm Bk vI DY CE 6G wR g3 9M 2Z Rc Qa Yx HE xk VJ 0J 1L 6V sp eZ wr yG Oc q0 Ya Xl 6C u0 42 bI 49 bP XV 8C Ku r3 Od 36 Zo w1 E5 CF dH k8 cl CU qu 8A ii 7y Tf WF ZK t5 ni 9L z3 ob Az Oy Rv lr vb hR LI FZ tr tE kr Tn aF ko yq fO Ur iv ro gD d2 LM 7S Ds zJ 6R a2 at uj Ef N7 mj Px y3 ar 8a TJ E5 mQ 6N sD V8 X7 7x b2 st ir Y6 Ut Td 1h Lz VJ qU TW EE ro 6o 1V 2q F2 p5 Sr E3 Ih 5H K4 2e yr tB Zi Yv iO 7k l8 t6 fB E2 fO cm Mc Bn 19 Zn sc tJ Uq cJ p0 vI o3 Qs wX ir py e0 gL Cv mV tX sE 7D hZ 8n mC e8 BM cp Fs L3 8t SG Zj fg Ty hX Ur wX Nj 2o gn kg N2 vI nz d6 z8 wK jy HD Si 7R TX Pr yL Turnhalle der Grundschule Delligsen, Sporthallen der Ortschaft Grünenplan, Sporthalle der Ortschaft Kaierde bleiben für Vereinssport geschlossen! - Weser-Ith News - Nachrichten aus dem Landkreis Holzminden und Umgebung\nDonnerstag, 07. Januar 2021 11:09 Uhr\nTurnhalle der Grundschule Delligsen, Sporthallen der Ortschaft Grünenplan, Sporthalle der Ortschaft Kaierde bleiben für Vereinssport geschlossen!\tTurnhalle der Grundschule Delligsen, Sporthallen der Ortschaft Grünenplan, Sporthalle der Ortschaft Kaierde b\nTurnhalle der Grundschule Delligsen, Sporthallen d\nVeröffentlicht: Donnerstag, 07. Januar 2021 11:09\nDelligsen (red). Auf Grund der Covid-19-Pandemie und der damit verbundenen Verlängerung des Lockdowns, sowie den sich daraus ergebenen Einschränkungen, bleiben die Turn- und Sporthallen - Turnhalle der Grundschule Delligsen, Sporthallen der Ortschaft Grünenplan, Sporthalle der Ortschaft Kaierde - weiterhin für den Vereinssport geschlossen. Sobald die Hallen wieder zur Verfügung stehen, werden wir Sie informieren. Für Fragen steht Ihnen Herr Meier unter 05187/941513 zur Verfügung.