trying to decrease overfitting with regularisation in CNN
Steps for overcoming overfitting are the followings:  

 1. Add more data  
 2. Use data augmentation  
 3. Use architectures that generalize well  
 4. Add regularization  
 5. Reduce architecture complexity.


I would try to add Dropout, lately it is being the most used regularization technique in complex networks architectures. Start adding it in the later layers, since it is best no to lose initial info. Something like 0.6 or like that, and if it is not enough add dropout in the previous layer, and so on.