<p>You might want to have a look at my masters thesis <a href="https://arxiv.org/pdf/1707.09725.pdf" rel="nofollow noreferrer">Analysis and Optimization of Convolutional Neural Network Architectures</a>, chapter 2.5 page 15:</p>

<blockquote>
  <p>A machine learning developer has the following choices to improve the model’s quality:<br/>
  (I1) Change the problem definition (e.g., the classes which are to be distinguished)<br/>
  (I2) Get more training data<br/>
  (I3) Clean the training data<br/>
  (I4) Change the preprocessing (see Appendix B.1)<br/>
  (I5) Augment the training data set (see Appendix B.2)<br/>
  (I6) Change the training setup (see Appendices B.3 to B.5)<br/>
  (I7) Change the model (see Appendices B.6 and B.7)</p>
</blockquote>

<p>It's always good to check thoroughly where exactly the problem is and compare it with a human baseline. Reliably getting better than a human is super hard.</p>
Steps to think of while trying to increase accuracy of network
<p>How do you proceed to increasing accuracy of your neural network?</p>

<p>I have tried lots of architectures yet in my image detection ( classification + localization ) I can only get 75% accuracy.</p>

<p>I am using VOC2007 dataset, and I extracted only data where 1 person is present.</p>

<p>What are the steps I can think of to increase the accuracy of my object detector?</p>

<p>thanks for help.</p>