I'm doing a two-class image segmentation problem using fully convolutional networks, and got the following
loss curves and
learning_rate change curves. From the
loss curves, it seems the network is overfitting from the training set. I have used the weight decay and changing learning rate policy. Are there any other methods to preventing the overfitting problem?
loss curves for training data and validation data are (blue line is loss curve on validation data):
learning_rate policy is piece-wise changing. It seems lowering the learning rate cannot change the loss values a lot.