Implementation of the stacked denoising autoencoder in Tensorflow

Paper Detecting anomalous events in videos by learning deep representations of appearance and motion on python, opencv and tensorflow. This paper uses the stacked denoising autoencoder for the the feature training on the appearance and motion flow features as input for different window size and using multiple SVM as a single c

Stacked Denoising Autoencoders (SDA) implemented in TensorFlow to analyze clinical health records and construct deep learning models to predict future patient complications.

Stacked Denoising AutoEncoder based on TensorFlow

My first code for Stacked Denoising Autoencoder using Keras with Tensorflow backend

An approach to classify hardware requests using a Stacked Denoising Autoencoder with TensorFlow

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Implementation of Stacked Denoising Autoencoders for TensorFlow

A Stacked Denoising Autoencoder built with TensorFlow/Keras for image restoration on Fashion MNIST. Features latent space visualization using t-SNE and performance evaluation with SSIM.