BCVM | RNNs in Computer Vision | Ravi Kiran, IISc - Part I

The talk covers the below topics 1. Motivation for Recurrent Neural Networks (RNNs) 2. RNN - usage paradigms, formulation, learning 3. Drawbacks of RNN, motivation and design evolution for LSTM 4. RNN/LSTM-based architectures in computer vision 5. RNN vs CNN revisited, RNNs v/s HMM 6. A case study: RNNs for on-line recognition of hand-drawn sketches About the speaker Ravi is a PhD student at IISc (Video Analytics Lab). Before joining IISc, he worked as a Research Engineer at Duos Technologies, USA from May 2012 to December 2013. Prior to that, he was a Research Engineer at Honda Research Institute USA from January 2008 to April 2012. He completed his masters in Computer Science from the University of Washington in 2008. He got an integrated MS/B.Tech degree (Honors) in Computer Science from IIIT-H in 2004. Please post your questions as comment