I am working on a hybrid CNN-SVM where I aim to use CNN for feature extraction and SVM for classification. However, I am confused as after reading related works, I found many approaches:
-Some use SVM instead of the softmax layer.
-Some use SVM after flatten layer.
-Others replace the activation function from softmax to linear and the loss function from cross entropy to L1-SVM.
So I wanted to know which method is the correct one among these approaches.