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Domain Enriched Learning for Image Processing and Computer Vision

Event Date: October 30, 2018
Speaker: Vishal Monga
Speaker Affiliation: Electrical Engineering
& Computer Science
Pennsylvania State University
Time: 3:30 pm
Location: MSEE 239
Priority: No
School or Program: Electrical and Computer Engineering
College Calendar: Show

Vishal Monga
Electrical Engineering and Computer Science
Pennsylvania State University

This talk will survey current research activity in the Information Processing and Algorithms (iPAL) Lab at Penn State. Two topics will get particular attention: 1.) dictionary learning with physically meaningful constraints for applications in image and object classification, and 2.) regularized deep networks which incorporate domain specific information and priors to enhance performance of compelling computer vision problems such as image super-resolution and segmentation.  

Professor Vishal Monga has been on the EECS faculty at Penn State since Fall 2009. From Oct 2005-July2009 he was an imaging scientist with Xerox Research Labs. He has also been a visiting researcher at Microsoft Research in Redmond, WA and a visiting faculty at the University of Rochester. Prior to that, he received his PhDEE from the department of Electrical and Computer Engineering at the University of Texas, Austin. Dr. Monga is an elected member of the IEEE Image Video and Multidimensional Signal Processing (IVMSP) Technical Committee and has served on numerous editorial boards including the IEEE Transactions on Image Processing, IEEE Signal Processing Letters and IEEE Transactions on Circuits and Systems for Video Technology. Professor Monga's research has been recognized via the US National Science Foundation CAREER award. For his educational efforts, Dr. Monga received the 2016 Joel and Ruth Spira Teaching Excellence award. His group’s work focuses on convex and non-convex optimization based methods with applications in learning, vision and signal processing.

Jan Allebach,, 49-43535