links.txt

links

http://scikit-learn.org/stable/index.html

http://deeplearning.net/demos/

# great starting point for convolutional nn for 2d image recognition
https://code.google.com/p/cuda-convnet2/

http://www.imbe.med.uni-erlangen.de/ma/M.Schmid/Tutorial/01_Introduction.pdf
https://www.youtube.com/watch?v=UHBmv7qCey4
http://www.cs.toronto.edu/~hinton/MatlabForSciencePaper.html
https://code.google.com/p/cuda-convnet2/

http://caffe.berkeleyvision.org/
https://github.com/Yangqing/caffe/wiki/Setting-up-Caffe-on-Ubuntu-14.04

http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial

http://deeplearning.net/tutorial/contents.html
http://deeplearning.net/tutorial/lenet.html
http://deeplearning.net/tutorial/mlp.html
http://deeplearning.net/software/theano/index.html
http://benanne.github.io/2014/04/03/faster-convolutions-in-theano.html

http://deeplearning.net/software/pylearn2/

# coursera classes
https://class.coursera.org/neuralnets-2012-001

# Hacker's guide to Neural Networks
http://karpathy.github.io/neuralnets/

# javascript demo 
http://cs.stanford.edu/people/karpathy/convnetjs/ 

#selective search
https://ivi.fnwi.uva.nl/isis/publications/bibtexbrowser.php?key=UijlingsIJCV2013&bib=all.bib



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computer vision

jsfeat

good blog on computer vision
http://www.pyimagesearch.com/

http://computer-vision-talks.com/

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Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
http://arxiv.org/pdf/1406.4729v1.pdf