I need to implement a classification application for neuron-signals. In the first step, I need to train a denoising autoencoder(DAE) layer for signal cleaning then, I will feed the output to a DBN network for classification. I tried to find support for these types in Tensorflow but all what I found was two models CNN and RNN. Does anyone has an idea about a robust implementation for these two models using Tensorflow?
Deep Belief Network with Denoising Auto Encoder in Tensorflow
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