Number of layers: the autoencoder can be as deep as we like. In the figure above we have 2 layers in both the encoder and decoder, without considering the input and output. Number of nodes per layer: ...

In this project, there are implementations for various kinds of autoencoders. The base python class is library/Autoencoder.py, you can set the value of "ae_para" in the construction function of ...

A stacked autoencoder can be implemented by using a sequential model that contains multiple encoder-decoder pairs, and using a greedy layer-wise training strategy, ...

Stacked Autoencoder based Intrusion Detection System using One-Class Classification Abstract: The paper presents a study of deep learning based approach for Intrusion Detection System. Already ...

Autoencoder is a widely used deep learning method, which first extracts features from all data through unsupervised reconstruction, and then fine-tunes the network with labeled data. However, due to ...