Update README.md

README.md

@@ -20,7 +20,7 @@ See [github.com/Cadene/pretrained-models.pytorch#resnext](https://github.com/Cad
 
 The segmentation model was first trained on ImageNet ([Deng et al., 2009](https://doi.org/10.1109/CVPR.2009.5206848)), and then the model was fine-tuned on a specific set of image data relevant to the domain: [Illinois Natural History Survey Fish Collection](https://fish.inhs.illinois.edu/) (INHS Fish). 
 The Feature Pyramid Network (FPN) architecture was used for fine-tuning, since it is a CNN-based architecture designed to handle multi-scale feature maps (Lin et al., 2017: [IEEE](https://doi.org/10.1109/CVPR.2017.106), [arXiv](https://doi.org/10.48550/arXiv.1612.03144)). 
-The FPN uses SE-ResNeXt as the base network (Hu et al., 2018: [IEEE](https://doi.org/10.1109/CVPR.2018.00745), [arXiv](https://arxiv.org/abs/1709.01507)).
+The FPN uses SE-ResNeXt as the base network (Hu et al., 2018: [IEEE](https://doi.org/10.1109/CVPR.2018.00745), [arXiv](https://doi.org/10.48550/arXiv.1709.01507)).
 
 
 ### Model Description
@@ -202,7 +202,7 @@ We had 99 testing images and 98 validation images.
 
 <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
 
-<!-- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+<!-- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://doi.org/10.48550/arXiv.1910.09700).
 
 - **Hardware Type:** [More Information Needed]
 - **Hours used:** [More Information Needed]