Slides: Stanford's CS231n: Convolutional Neural Networks for Visual Recognition

Fei-Fei Li and Andrej Karpathy taught CS231n: Convolutional Neural Networks for Visual Recognition at Stanford. The whole set of slides is here. Lots of interesting things, in particular the slides at the end of the course that connect to very recent papers some of which we have mentioned here. Here they are:

• What makes ConvNets tick, Transfer Learning [slides] [notes]
• Squeezing out the last few percent, Training ConvNets in practice [slides]
• Beyond Image Classification: localization, detection, segmentation. Recurrent Networks I: Image Captioning example [slides]
• Invited Speaker: Evan Shelhamer: Working with Caffe, an open-source ConvNet library [slides]
• Invited Speaker: Lubomir Bourdev, Facebook AI Research
• Invited Speaker: Jon Shlens, Google Brain [slides]
• Working with Caffe: hands-on tutorial with Justin [slides] [code] [coco_animals (3.9GB)]
• Mystery talk, Tiny ImageNet student spotlights, Recurrent Networks II, Attention Models [slides][Tiny ImageNet leaderboard]

Join the CompressiveSensing subreddit or the Google+ Community and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.