# What to do next for preventing the overfitting?

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?

The loss curves for training data and validation data are (blue line is loss curve on validation data):

The learning_rate policy is piece-wise changing. It seems lowering the learning rate cannot change the loss values a lot.