title: Is Bias necessarily need at Colvolution Layer?
body: <p>I'm building CNN + Ensemble model for classify images with Tensorflow at Python. I crawled dog and cat images at google images. Then changed them to 126 * 126 pixel size and gray scale, add label 0 to dog, 1 to cat. CNN has 5 conv layer and 2 fc layer. HE, PReLU, max-pooling, drop-out, Adam are used in model. When Parameter Tuning finished, I added Early-Stopping, the model learned 65~70 epoch, finished with 92.5~92.7% accuracy. 
  After learning finished, I want change my CNN model to VGG network, I checked my CNN parameter, shockingly, I found I didn't add Bias at conv layer. 2 fc layer had Bias but 5 conv layer didn't have Bias. So I added Bias at 5 conv layer, BUT my model could not learn. Cost increased to infinite.</p>
  
  <p>Bias is not necessarily at Deep Convolution Layer?</p>