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awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-deep-vision

A curated list of deep learning resources for computer vision

awesome-python-cn

Python资源大全中文版，内容包括：Web框架、网络爬虫、网络内容提取、模板引擎、数据库、数据可视化、图片处理、文本处理、自然语言处理、机器学习、日志、代码分析等

benchmark_results

visual tracker benchmark results

caffe

Caffe: a Fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.

caffe2

This is currently an experimental refactoring of Caffe.

cf2

Hierarchical Convolutional Features for Visual Tracking (ICCV 2015)

darknet

Convolutional Neural Networks

deep-residual-networks

Deep Residual Learning for Image Recognition

deepframeworks

Evaluation of Deep Learning Frameworks

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.

dense_flow

fast-rcnn

Fast R-CNN

faster_rcnn

Faster R-CNN

fcnt

gdlnotes

Google Deep Learning笔记（TensorFlow）

goturn

Source code for paper: Learning to Track at 100 FPS with Deep Regression Networks, Held, et al. ECCV 2016

gsoc11_tracking

port of http://code.google.com/p/gsoc11-opencv-tracking/ to proper OpenCV

jquery

jQuery JavaScript Library

lct-tracker

Long-term Correlation Tracking in CVPR 2015

leek

My repository on GitHub

locnet

LocNet: Improving Localization Accuracy for Object Detection

machine-learning

my machine-learning tutorial

mdnet

Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

opentld

Official source code for TLD

overfeat

python

All Algorithms implemented in Python

python-cookbook

Code samples from the "Python Cookbook, 3rd Edition", published by O'Reilly & Associates, May, 2013.