How Machines 'See' the World

Dr. Kaiman Zeng
Assistant Professor EE Department, Arkansas Tech University, Russellville, AR

Cerent Engineering Science Complex, Salazar Hall 2009A
3:00 PM

Abstract – Vision might be the most important sense for our humans. Visual perception provides us an understanding of our surroundings and help interact with the surroundings. In order to build smart machines to perform intelligent work for us, enabling machine vision plays a central role. Thanks to recent advances in deep learning, big data, and supercomputers, we start to have the capabilities of empowering machines see the world like us. The performances of some classic tasks in computer vision, such as image recognition and object detection, have been significantly boosted. This talk will discuss the research challenges, state-of-the-art deep learning models, and their applications in classic computer vision tasks.

Dr. Kaiman Zeng is an Assistant Professor in the Department of Electrical Engineering at Arkansas Tech University. She received her Ph.D. degree from the Department of Electrical and Computer Engineering at Florida International University. Her research interests include digital image processing, computer vision, machine learning, and engineering education.