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agnet

The code of "Attention Guided Network for Retinal Image Segmentation" in MICCAI 2019

ai-job-notes

AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

beam-propagation-method

bm3d

bm3d-denoise

Using BM3D to denoise ,the code I'm modified is from https://github.com/MarkPrecursor/BM3D_Denosing.git

bm3d-gpu

CUDA implementation of BM3D

bp_cuda

Handwritten Numeral Recognition with ANN

coding-note

刷题笔记：LeetCode和剑指Offer等

cookie

cvpr2019

cvpr2019／cvpr2018/cvpr2019 papers，极市团队整理

cvpr2020-code

CVPR 2020 论文开源项目合集

daily-paper-computer-vision

记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文

deep-learning-interview-book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

deepdyn

pytorch based framework for Convolutional Neural Network

deeplearningbook-chinese

Deep Learning Book Chinese Translation

deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

deformable-convnets

Deformable Convolutional Networks

detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

dncnn

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)

dogs_vs_cats

猫狗大战

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fr-srgan

Class Final Project for MIT 6.819 Advances in Computer Vision

image-super-resolution

🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

image_segmentation

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

isic2018

Lesion attributes segmentation for melanoma detection with multi-task U-Net

it_book

本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）

laddernet

laser-speckle-contrast

Processing Procedure of Laser Speckle Contrast，matlab