BCDU-Net : Medical Image Segmentation

HDR image reconstruction from a single exposure using deep CNNs

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

anomaly detection by one-class SVM

[SIGGRAPH Asia 2017] High-Quality Hyperspectral Reconstruction Using a Spectral Prior

SegNet-like Autoencoders in TensorFlow

A convolutional autoencoder made in TFLearn.

Unsupervised deep learning system for local anomaly event detection in crowded scenes

Implementation of a convolutional auto-encoder in PyTorch

Gaussian Mixture Convolutional AutoEncoder applied to CT lung scans from the Kaggle Data Science Bowl 2017

Image Denoising Using Deep Convolutional Autoencoder with Feature Pyramids

Convolutional autoencoder for encoding/decoding RGB images in TensorFlow with high compression ratio

A convolutional auto-encoder for compressing time sequence data of stocks.

Micro neural network with multi-dimensional layers, multi-shaped data, fully or locally meshing, conv2D, unconv2D, Qlearning, ... for test!

High Dynamic Range Image Synthesis via Attention Non-Local Network

Music Xtraction with Nonstationary Gabor Transforms and Convolutional Denoising Autoencoders

Implementation of Cancelable Biometric Template Generation using Convolutional Autoencoder

Collection of autoencoder models in Tensorflow

Time Series Forecasting using RNN, Anomaly Detection using LSTM Auto-Encoder and Compression using Convolutional Auto-Encoder