SegNet-like Autoencoders in TensorFlow
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Updated
Feb 27, 2017 - Python
SegNet-like Autoencoders in TensorFlow
This is implementation of convolutional variational autoencoder in TensorFlow library and it will be used for video generation.
A simple feedforward neural network based autoencoder and a convolutional autoencoder using MNIST dataset
Gaussian Mixture Convolutional AutoEncoder applied to CT lung scans from the Kaggle Data Science Bowl 2017
A convolutional auto-encoder for compressing time sequence data of stocks.
Experiments that accompany a paper in which Transfer-Learning applied to GAN is examined
Unsupervised Image Retrieval with Convolutional Autoencoder in Tensorflow
We use the Convolutional AutoEncoder Network model to train animated faces 👫 and test from a random noise added to the original image as input (to check if it performs on noised inputs).
A convolutional autoencoder made in TFLearn.
Convolutional autoencoder for encoding/decoding RGB images in TensorFlow with high compression ratio
Cost function and cost gradient function for a convolutional autoencoder.
Convolutional Autoencoder for Denoising Images
Implementation of a convolutional auto-encoder in PyTorch
A previous project based on tensorflow in COMP 5212, HKUST. The project includes user-customized momentum SGD optimizer, CNN and CAE (convolutional autoencoder).
[SIGGRAPH Asia 2017] High-Quality Hyperspectral Reconstruction Using a Spectral Prior
Image Compression on COCO Dataset using Convolution AutoEncoders
This project demonstrates how CAE can be implemented in tensorflow framework. The dataset used is Fashion-MNIST Dataset.
A python based machine learning toolkit for recovering the kinematic disorder of galaxies based on their velocity maps as well as returning an inclination-dependent position angle prediction for further kinematic modelling.
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