I intend to make a classifier using the feature map obtained from a CNN. Can someone suggest how I can do this?
Would it work if I first train the CNN using +ve and -ve samples (and hence obtain the weights), and then every time I need to classify an image, I apply the conv and pooling layers to obtain the feature map? The problem I find in this, is that the image I want to classify, may not have a similar feature map, and hence I wouldn't be able to find the distance correctly. As the order of the features may by different in the layer.