报告题目：IPR and Applications to e-Forensics and Smart Cities
Patrick Wang, Fellow of IAPR, ISIBM, WASE, and IETI, has been tenured full professor of Computer & Information Science at Northeastern U, USA, MIT & Harvard U adjunct Faculty, Shanghai East China Normal University Zi-Jiang Visiting Chair Professor, research consultant at MIT, and adjunct faculty of computer science at Harvard University. He received PhD in C.S. from Oregon State U, M.S. in I.C.S. from Georgia Institute of Tech, M.S.E.E. from National Taiwan U and B.S.E.E. from National Chiao Tung U (Taiwan) 新竹交大.
As IEEE and ISIBM Distinguished Achievement Awardee, Dr. Wang was on the faculty at University of Oregon and Boston U, and senior researcher at Southern Bell, GTE Labs and Wang Labs. Dr. Wang was Otto-Von-Guericke Distinguished Guest Professor of Magdeburg U, Germany, and iCORE (Informatics Circle of Research Excellence) visiting professor of U of Calgary, Canada, Honorary Advisor Professor for China’s Sichuan U, Chongqing U, and Guangxi Normal U, Guilin, Guangxi. In addition to his research experience at MIT AI Lab, Dr. Wang has published over 300 technical papers and 26 books in Pattern Recognition, A.I. Biometrics and Imaging Technologies and has 3 OCR patents by US and Europe Patent Bureaus.
This talk is concerned with fundamental aspects of Intelligent Pattern Recognition (IPR) and applications. It basically includes the following: Basic Concept of Automata, Grammars, Trees, Graphs and Languages. Ambiguity and its Importance, Brief Overview of Artificial Intelligence (AI), Brief Overview of Pattern Recognition (PR), What is Intelligent Pattern Recognition (IPR)? Interactive Pattern Recognition Concept, Importance of Measurement and Ambiguity, How it works, Modeling and Simulation, Basic Principles and Applications to Computer Vision, Security, e-Forensics, Road Sign Design, biomedical diagnosis, Safer biomedical diagnosis, Traffic and Robot Driving with Vision, Ambiguous (design of Road Signs vs Unambiguous (Good) Road Signs, How to Disambiguate an Ambiguous Road Sign? What is Big Data? and more Examples and Applications of Learning and Greener World using Computer Vision. Finally, some future research directions are discussed.