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Computer Vision: Learning to See
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Computer Vision: Learning to See
Zhengping Ji (Ph.D)
Advanced Image Research Lab,Samsung Electronics,USA

Address:JC-B507

Time:   2015/7/31,9:30 am

Abstract
Computer vision delivers representation, conducts interpretation, and enables understanding of images, videos, and in general high dimensional data that is captured for visual scene of real world. In this talk, I will discuss building blocks of computer vision, with respect to image acquisition, image representation, along with models and algorithms to transform numerical representations for symbiotic concepts.  Part of our contribution in this field will be described, in particular sparse coding and deep learning. The techniques presented will cover broad application fields, including but not limited to, image denoising, image restoration, super resolution, vision-based biometrics, visual recognition and segmentation, content-based image retrieval, autonomics driving and humanoid robotics.

Biography
Zhengping Ji is now a Staff Research Scientist at Advanced Image Research Lab of Samsung Electronics. He received his B.S. degree in Electrical Engineering from Sichuan University, and the Ph.D. in Computer Science from Michigan State University, USA. After that, he held a Postdoctoral Fellow position at the Center for the Neural Basis of Cognition, Carnegie Mellon University, working on the DARPA RealNose Project. Before joining Samsung, he was  a Research Associate at  Los Alamos National Laboratory to conduct researches on computational modeling of the brain’s visual pathways.
His current research interests lie in computer vision, computational neuroscience and machine learning. Specifically, he seeks to develop a series of deep learning models to generate cortex-like hierarchical sparse representation for a variety of tasks in vision, including generic object recognition, object detection and segmentation, image denoising and compression, and vision-based autonomous navigation. He is a Vice Chair of Task Force on Bio-Inspired Self-Organizing Collective Systems at IEEE Computational Intelligence Society, and a committee member of the Brain-Mind Institute, USA. He served the Guest Editor of the special issue of Journal of Robotics and Autonomous System, as well as program committee members and secession chairs for a number of international conferences and workshops.