Scalable Learning in Computer Vision
published: Jan. 19, 2010, recorded: December 2009, views: 444
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Computer vision is a challenging application area of machine learning. Recent work has shown that large training sets may yield higher performance in vision tasks like object detection. We overview our work in object detection using a scalable, distributed training system capable of training on more than 100 million examples in just a few hours. We also briefly describe recent work with deep learning algorithms that may allow us to apply these architectures to large datasets as well.
Download slides: nipsworkshops09_coates_slcv_01.pdf (1.3 MB)
Download slides: nipsworkshops09_coates_slcv_01.ppt (3.0 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !