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I am working on a multiclass multilabel image classification problem. I am using a pre-trained CNN from model zoo to perform feature extraction, as here Caffe Docs
Despite trying a several different
pre-trained CNNs, performance on the test data has maxed out.The pre-trained CNNs are trained on completely different sets of
images than those that I am trying to classify. Therefore, I am
wondering if the features that they are extracting are sufficient rich.
I have my own CNN that I trained on the specific training images of
this multilabel problem. It has very good performance on the training
set, but I never managed to get it to generalize to the validation set
(so I decided not to use it directly). What about using this CNN as a
feature extractor? Thanks!