I am using Indian Pines as the test hyperspectral data for image classification. I have already done classical methods like Gaussian Mixture , SVM and Random Forest classifier.

Now , moving onto Autoencoder method , I want to classify Indian pines dataset (16 classes) using stacked or sparse architecture of Autoencoder.

I have used keras library to build up some code.

Are there any other simpler ways than use softmax classification.

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