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3d-ru-net

A SlidingWindow-Free Accurate and Fast 3D Medical Image Segmentation Framework

adam-experiments

Experiments with Adam/AdamW/amsgrad

adamwr

Implements https://arxiv.org/abs/1711.05101 AdamW optimizer and cosine learning rate scheduler for PyTorch framework

adaptive_affinity_fields

Adaptive Affinity Fields for Semantic Segmentation

afnet

Code for paper in CVPR2019, 'Attentive Feedback Network for Boundary-aware Salient Object Detection'

augmentor

Image augmentation library in Python for machine learning.

automatic-salt-deposits-segmentation

awesome-cmake

A curated list of awesome CMake resources, scripts, modules, examples and others.

awesome-cpp

A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

awesome-data-augmentation

This is a list of awesome methods about data augmentation.

awesome-pytorch-list-cnversion

Awesome-pytorch-list 翻译工作进行中......

awesome-super-resolution

Collect super-resolution related papers, data, repositories

awsrn

PyTorch code for our paper "Lightweight Image Super-Resolution with Adaptive Weighted Learning Network"

batchgenerators

A framework for data augmentation for 2D and 3D image classification and segmentation

bcrf-detectron

brats17

Brain tumor segmentation for MICCAI 2017 BraTS challenge

catalyst

Reproducible and fast DL & RL.

classifier-balancing

This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

cmake-examples

Useful CMake Examples

cmake-tutorial

CMake 官方教程

cnnmrf-pytorch

cs_offer

计算机学科基础知识和主流编程语言相关内容的总结

cuda-sample

CUDA official sample codes

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cutmix-pytorch

Official Pytorch implementation of CutMix regularizer

cutout

2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552

cvpr2019

cvpr2019 papers

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。

data-science-competitions

Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).