What loss function to use in CNN-SVM model

Question

I am using Matlab R2018b and am trying to infuse SVM classifier within CNN. My plan is to use CNN only as a feature extractor and use SVM as the classifier. I know people have already implemented it a few years back either in tensorflow or in other platforms. In implementing this I got stuck at a point during backward propagation. I got puzzled about which loss function I need to implement to upgrade the gradients and the parameters.

Few points came up during this:

1. I got a feeling to implement the hinge loss here. But which form of hinge loss should I implement? Should I move on to the second form of hinge loss implementation for calculating loss during backward propagation?

2. Besides, calculating the backward loss, should I calculate the forward loss as well to find out the loss occurred in the model?

Any form of advice doing this CNN-svm infusion will be appreciated as I am unable to find any such material implemented in Matlab to get help.

Thanks.

Comments

Quick question, why should you use SVM and implement the backpropagation? Why do not use the libraries?