My Reading list-machine Learning && Computer Vision

This blog summarizes the individual in the learning process of some of the papers, code, materials and common resources and sites, in order to facilitate the recording of their own learning process, put it in the blog.

Machine learning

(1) Machine learning Video Library-caltech
Description: A list of common algorithms for machine learning and machine learning maps

(2) Deep Learning-bengio

Description: Deep learning one of the three Daniel Bengio wrote a book

(3) Understanding LSTM Networks

Description: Very good lstm tutorial

(4) Hacker ' s Guide to Neural Networks

Description: Standford University CS PhD Andrej Karpathy written by neural Network Learning Guide

(5) The unreasonable effectiveness of recurrent neural Networks

Description: The same Andrej Karpathy wrote about RNN's blog

Computer Vision

Detction Project

(1) RCNN:

Paper:http://www.cs.berkeley.edu/~rbg/papers/r-cnn-cvpr.pdf

Code:https://github.com/rbgirshick/rcnn

(2) FAST-RCNN:
Paper:http://arxiv.org/pdf/1504.08083v1.pdf

Code:https://github.com/rbgirshick/fast-rcnn

(3) FASTER-RCNN:
Paper:http://arxiv.org/pdf/1506.01497v1.pdf

Code:unrelease

(4) Spp-net:
Paper:http://arxiv.org/pdf/1406.4729v4.pdf

Code:https://github.com/shaoqingren/spp_net

(5) YOLO:

Paper:http://arxiv.org/pdf/1506.02640v3.pdf

code:http://pjreddie.com/darknet/yolo/

(6) Target detection method combining end-to-end people detection in crowded SCENES:CNN and lstm

Paper:http://arxiv.org/pdf/1506.04878v3.pdf

Code:https://github.com/russell91/reinspect

Tracking

(1) CMT:
Paper:

Cvpr2014:http://www.gnebehay.com/publications/cvpr_2015/cvpr_2015.pdf

Wacv2014:http://www.gnebehay.com/publications/wacv_2014/wacv_2014.pdf

website:http://www.gnebehay.com/cmt/

Code:

Python:https://github.com/gnebehay/cmt

C + +: Https://github.com/gnebehay/CppMT

Helpful Blog:

songrotek:http://blog.csdn.net/songrotek/article/details/47662617

superresolution

(1) SCSR
paper:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4587647
Code:http://www.ifp.illinois.edu/~jyang29/codes/scsr.rar
Website:http://www.ifp.illinois.edu/~jyang29/scsr.htm

(2) SRCNN
Paper:
Eccv2014:http://personal.ie.cuhk.edu.hk/~ccloy/files/eccv_2014_deepresolution.pdf
t-pami:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7115171
Website:http://mmlab.ie.cuhk.edu.hk/projects/srcnn.html
Code:http://mmlab.ie.cuhk.edu.hk/projects/srcnn.html

people

(1) Ross B. girshick-the Author of Rcnn, FAST-RCNN
website:http://www.cs.berkeley.edu/~rbg/#girshick2014rcnn
Github:https://github.com/rbgirshick

(2) shaoqing ren-the Author of FASTER-RCNN, spp-net
website:http://home.ustc.edu.cn/~sqren/
Github:https://github.com/shaoqingren

(3) Georg nebehay-the Author of CMT
Website:http://www.gnebehay.com
Github:https://github.com/gnebehay

(4) Jianchao yang-the Author of SCSR
website:http://www.ifp.illinois.edu/~jyang29/

interestiing Things

(1) Panoramic view
m.s_2308
Description: http://www.guokr.com/post/444888/
Analysis: http://www.guokr.com/post/445059/
Software: http://matthewalunbrown.com/autostitch/autostitch.html

(2) Kaggle competition:denoising Dirty Documents
Proplem Website:https://www.kaggle.com/c/denoising-dirty-documents/data
Solution website:http://colinpriest.com/

My Reading list-machine Learning && Computer Vision