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31 search results found

Niftynet ⭐ 1,170

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Easy Deep Learning With Keras ⭐ 336

Keras tutorial for beginners (using TF backend)

Handson Ml ⭐ 277

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Minimalist implementation of VQ-VAE in Pytorch

Deep Steganography ⭐ 125

Hiding Images within other images using Deep Learning

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Mad Twinnet ⭐ 101

The code for the MaD TwinNet. Demo page:

Implementation of the Sliced Wasserstein Autoencoders

Video_generator ⭐ 63

This is implementation of convolutional variational autoencoder in TensorFlow library and it will be used for video generation.

Swae Pytorch ⭐ 59

Implementation of the Sliced Wasserstein Autoencoder using PyTorch

Lipreading ⭐ 42

A Deep Learning Framework For Assessing Physical Rehabilitation Exercises ⭐ 41

A framework for quality assessment of exercises in physical rehabilitation based on skeletal joint displacements collected with a motion capture system.

Conditional_vae ⭐ 37

conditional variational autoencoder written in Keras [not actively maintained]

Unsupervised Deep Architechtures in R

Contractive_autoencoder_in_pytorch ⭐ 34

Pytorch implementation of contractive autoencoder on MNIST dataset

Neural network library written in C and Javascript

Pytorch Recurrent Ae Siggraph17 ⭐ 29

Pytorch implementation for 'Interactive Reconstruction of Monte Carlo Image Sequences using a Recurrent Denoising Autoencoder' , https://research.nvidia.com/publication/interactiv

Neural Text Style Transfer ⭐ 29

Style Transfer for non-parallel text

Image_deionising_auto_encoder ⭐ 25

Noise removal from images using Convolutional autoencoder

Deep Learning Visuals ⭐ 24

A collection of 100 Deep Learning images and visualizations

Deeplearningexamples ⭐ 22

Deep learning examples with Python and Tensorflow & Keras.

Propertyclassification ⭐ 20

Classifying the type of property given Real Estate, satellite and Street view Images

Stackeddae ⭐ 20

Stacked Denoising AutoEncoder based on TensorFlow

Deep_learning_fmri_eeg ⭐ 18

Implementation of deep learning models in decoding fMRI/EEG data in a context of semantic processing

Continuous_bernoulli ⭐ 18

A program of simulator and test statistic for continuous Bernoulli distribution. More than that, it contains two Continuous Bernoulli populations and continuous Trinomial distribution for variational autoencoder model in deep learning.

Concise Ipython Notebooks For Deep Learning ⭐ 17

Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

Introduction To Deep Learning And Neural Networks Course ⭐ 16

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

Transformers_unsupervised_anomaly_segmentation ⭐ 14

Transformer-based Models for Unsupervised Anomaly Segmentation in Brain MR Images

Opensw_camp_2020 ⭐ 13

2020년 공개SW 대학생 체험캠프

Simpleai ⭐ 12

A simple yet powerful C++17 implementation of deep neural networks from scratch.

Example of vanilla VAE for face image generation at resolution 128x128 using pytorch.

Deep Neural Network For Clustering ⭐ 8

Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique

Open-set Recognition with Adversarial Autoencoders

Data Science Projects ⭐ 8

{PySpark, R, Python}: Several Data Science projects

K Sparse Autoencoder ⭐ 8

Sparse Auto Encoder and regular MNIST classification with mini batch's

Lgn Autoencoder ⭐ 7

Lorentz group equivariant autoencoders based on Lorentz Group Network

Unknown_number_source_separation ⭐ 7

Source separation of underwater acoustic radiated noise signals from ships with unknown numbers of signals. Using keras 2.2.4 with tensorflow-gpu 1.12.0 backend.

Normative Modelling Using Deep Autoencoders ⭐ 6

Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and Alzheimer’s disease

Multiscale_variational_autoencoder ⭐ 6

Building a multiscale variational autoencoder

Python implementation of DNGR model (Deep Neural Networks for Graph Representations)

Modern Deep Network Toolkits for Tensorflow-Keras. This is a extension for newest tensorflow 1.x.

Deep Learning ⭐ 5

This repo is the continuation of the Machine-Learning repo. Here I'm gonna to upload all the examples and exercises which I'll do to learn deep learning techniques and all the problems I'll solve using these last few.

Autoencoder for multi-label classification using Google's Tensorflow framework and MDMR for feature selection.

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