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representation-learning-by-learning-to-count

A Tensorflow implementation of Representation Learning by Learning to Count

reproblems

A set of real-world multi-objective optimization problems

repulsion_loss_ssd

Repulsion Loss: Detecting Pedestrians in a Crowd. https://arxiv.org/abs/1711.07752

requests-for-research

A living collection of deep learning problems

research

comma.ai for the people to experiment with

reseg-pytorch

PyTorch Implementation of ReSeg (https://arxiv.org/pdf/1511.07053.pdf)

resemblyzer

A python package to analyze and compare voices with deep learning

resfgb

Functional gradient boosting based on residual network perception

reshapegan

Controllable Object Reshaping by Learning from Unpaired Multi-Domain Data

residual-of-residual-networks

Residual Network of Residual Networks in Keras

residual.mnist

resnet

Deep Residual Learning for Image Recognition, http://arxiv.org/abs/1512.03385

resnet-1

Reproduce ResNet-v2(Identity Mappings in Deep Residual Networks) with MXNet

resnet-1k-layers

Deep Residual Networks with 1K Layers

resnet-cppn-gan-tensorflow

Using Residual Generative Adversarial Networks and Variational Auto-encoder techniques to produce high resolution images.

resnet-in-tensorflow

Re-implement Kaiming He's deep residual networks in tensorflow. Can be trained with cifar10.

resnet_cnn_mri_adni

Code for Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification paper

resnext

Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) with Caffe

resnext-1

Implementation of a classification framework from the paper Aggregated Residual Transformations for Deep Neural Networks

resnext-densenet

Pytorch Implementation for ResNet, Pre-Activation ResNet, ResNeXt and DenseNet

resnext-tensorflow

Simple Tensorflow implementation of ResNeXt using Cifar10

rest

This is an official implementation for "ResT: An Efficient Transformer for Visual Recognition".

restrictedboltzmannmachine

Neural network trained as a generative model on the MNIST dataset using Persistent Contrastive Divergence.

resurrect3d

Cultural Heritage 3D Rendering Platform

rethinking-image-mixture-for-unsupervised-learning

Rethinking Image Mixture for Unsupervised Visual Representation Learning

retina-unet

Retina blood vessel segmentation with a convolutional neural network

retinet

retrieval-2016-deepvision

Faster R-CNN features for Instance Search

retrieval-2016-icmr

Bags of Local Convolutional Features for Scalable Instance Search (ICMR 2016)

retrieval-2016-remote

Multi-Label Remote Sensing Image Retrieval By Using Deep Features