- Date : 27 May. 2016, 14:00 ~
- Place : ITBT 508
- Title : Introduction to Deep Learning for Visual Recognition
- Speaker : Prof. Bohyung Han
Deep learning has been very successful in many visual recognition problems, and impressive algorithms with outstanding performance have been released every day. This lecture starts with very simple neural networks, where the concept of artificial neural networks and learning algorithm by error backpropagation are discussed using a few standard applications in computer vision, and discusses why neural networks have not been successful for a long time and what break-throughs are critical to recent advances. In addition, it deals with a basic convolutional neural network for image classification, AlexNet; its architecture, properties, and several techniques for performance enhancement are presented.
Bohyung Han received the B.S. and M.S. degrees from the Department of Computer Engineering at Seoul National University, Korea, in 1997 and 2000, respectively, and the Ph.D. degree from the Department of Computer Science at the University of Maryland, College Park, MD, USA, in 2005. He was with Samsung Electronics Research and Development Center, Irvine, CA, USA, and Mobileye Vision Technologies, Princeton, NJ, USA. He is currently an Associate Professor with the Department of Computer Science and Engineering at POSTECH, Korea. He served as an Area Chair in NIPS 2015, ICCV 2015, ACCV 2012/2014/2016, ACML 2016 and WACV 2014, and as a Demo Chair in ACCV 2014. His current research interests include computer vision and machine learning.