Abstract: Face recognition by machines can be invaluable with various important applications in real life, such as electronic and physical access control, national defense and international security. Machine learning of faces requires usually a facial image database where different face images of a person are included to account for variations in facial features. Current face recognition methods rely on: detecting local facial features and using them for face recognition (local recognition) or on analyzing a face as a whole (global recognition). However, despite the emergence of many methods and systems for face recognition over the past decade, we are still far from deploying such systems for our daily use.
Why are we still hesitant to rely on machine face recognition? What are the problems of face detection and recognition systems? What is the significance of facial databases? What can be done to make us trust a machine's decision over who is who? These questions and more will be discussed during the lecture. Moreover, we review the difference between local and global face recognition, and present two intelligent facial recognition systems which we developed based on the local and global recognition approaches.

Brief Biography of the Speaker:
Adnan Khashman received his Ph.D. and M.Sc. degrees in electronic engineering from University of Nottingham, England, UK, in 1992 and 1997, respectively, and his B.Eng. degree in electronic and communication engineering from University of Birmingham, England, UK, in 1991. During 1998-2001 he was an Assistant Professor and Chairman of the Computer Engineering Department, Near East University, Nicosia, N. Cyprus. During 2001-2009 he was an Associate Professor and Chairman of the Electrical and Electronic Engineering Department at the same university. From 2007 till 2008 he was also the Vice-Dean of the Engineering Faculty. Since 2009 he is a full Professor and the Head of the Intelligent Systems Research Group (ISRG) which he founded in 2001 at the same university.
His current research interests include emotion modeling in neural networks and their engineering applications, intelligent systems and their applications, image processing, and pattern recognition. Prof. Dr. Khashman is a Senior Member of IEEE, and a reviewer for many journals. He has authored and co-authored more than 65 scientific publications in books, journals, and conference proceedings.