Speaker

Prof. Sos Agaian

The City University of New York, USA
Fellow IEEE

Speech Title: Bio-Inspired Single-Image Quality Assessment: Bridging Human and Computer Vision

Abstract: Bio-inspired image processing draws from computational neuroscience, cognitive science, and biology to develop algorithms for real-world image processing systems, enabling computers to "see" as humans do. This interdisciplinary approach has led to the creating of various image-processing algorithms with different levels of alignment to biological vision studies. However, digital images undergo various distortions during acquisition, processing, transmission, compression, storage, and reproduction. How can we accurately and efficiently measure the quality of a single image, even without a reference?
This talk explores the cutting-edge perception-guided single-image quality assessment (IQA) field. We delve into how bio-inspired computation, drawing inspiration from human visual perception, revolutionizes IQA. We will cover (i) how models based on biological vision systems can provide novel, robust, and computationally efficient ways to assess image quality, (ii) a synopsis of the latest research and breakthroughs in single-image "blind" IQA, (iii) emerging technologies and potential commercial applications of bio-inspired IQA, and (iv) how these advancements will shape the future of visual technology, from photography and video to medical imaging and beyond. Participants will gain a comprehensive understanding of how bio-inspired computation is revolutionizing image quality assessment and optimization, ushering in a new era of visual technology.

Biography: Dr. Sos Agaian is a Distinguished Professor of Computer Science at the Graduate Center and the College of Staten Island, CUNY. Before joining CUNY, he was the Peter T. Flawn Professor at the University of Texas at San Antonio. He also served as a Visiting Professor at Tufts University and a Lead Scientist at Aware, Inc. in Massachusetts. His research spans computational vision, machine learning, AI, multimedia security, remote sensing, and biomedical imaging. Dr. Agaian has received funding from NSF, DARPA, Google, and other agencies. He has published over 850 articles, 10 books, and 19 book chapters and holds 56 patents/disclosures, many of which have been licensed. He has mentored 45 PhD students and received multiple awards for research and teaching, including the MAEStro Educator of the Year, the Distinguished Research Award, the Innovator of the Year, the Tech Flash Titans-Top Researcher Award, and recognition as an Influential Member of the School of Engineering at Tufts University. He is an Associate Editor for several journals, including the Image Processing Transaction (IEEE) and IEEE Transaction of Cybernetics. He is a fellow of the Society for Imaging Science and Technology (IS&T), the Optical Society of America (SPIE), the American Association for the Advancement of Science (AAAS), Institute of Electrical and Electronics Engineers (IEEE), The Asia-Pacific Artificial Intelligence Association (AAIA), and a Foreign Member of the Armenian National Academy. He has delivered over 30 keynote speeches, 100 invited talks, and co-founded/chaired over 200 international conferences. He has also been a Distinguished IEEE Systems, Man, and Cybernetics Society Lecturer.