Editorial

Machine learning and pattern recognition models in change detection

Dr. Djamel Bouchaffra received the Ph.D. degree in Computer Science from Grenoble University, France. He currently holds the title of Director of Research. In 2012, he joined the Center for Development of Advanced Technology, and in January 2013 he was appointed Head of the Division “Design and Implementation of Intelligent Machines” (former “Systems Architecture and Multimedia”). Prior to this appointment, Dr. Bouchaffra was a Professor of Computer Science at the Department of Mathematics and Computer Science, Grambling State University, LA. He was a Senior Lead Researcher at the Center of Excellence for Document Analysis and Recognition (CEDAR) at the University of New York, Buffalo. Prior to this appointment, Dr. Bouchaffra was an Assistant Professor at Oakland University, Michigan. He is currently working on mathematical models that embed discrete structures into a Euclidean space or a Riemannian manifold and merge topology with statistics for a classification or a regression task. He introduced the structural and the topological hidden Markov models. He has written many papers in peer-reviewed conference proceedings and premier journals, such as the IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transaction on Neural Networks and Learning Systems and Pattern Recognition. His current research interests include pattern recognition, machine learning, computer vision, and artificial intelligence. Dr. Bouchaffra was the lead Guest Editor of a special issue in the journal of Pattern Recognition titled “Feature Extraction and Machine Learning for Robust Multimodal Biometrics”, published by Elsevier. He is an Editorial Board Member of several journals, such as Pattern Recognition (Elsevier), and Advances in Artificial Intelligence (Hindawi). He chaired several sessions in conferences. He is on the review panels of governmental funding agencies, such as NASA (Galaxy Classification) and EPSRC, U.K.

Dr. Bouchaffra is an IEEE senior Member and a member of the IEEE Computer Society.

Dr. Mohamed Cheriet received his B.Eng. from USTHB University (Algiers) in 1984 and his M.Sc. and Ph.D. degrees in Computer Science from the University of Pierre et Marie Curie (Paris VI) in 1985 and 1988 respectively. Since 1992, he has been a professor in the Automation Engineering department at the University of Quebec׳s École de Technologie Supérieure (ÉTS), Montreal, and was appointed full professor there in 1998. He co-founded the Laboratory for Imagery, Vision and Artificial Intelligence at ÉTS, and was its director from 2000 to 2006. He also founded the SYNCHROMEDIA Consortium (Multimedia Communication in Telepresence) there, and has been its director since 1998. His interests include image processing and analysis, OCR, mathematical models for image processing, pattern classification models and learning algorithms, as well as perception in computer vision. Dr. Cheriet has published more than 300 technical papers in the field, and has served as chair or co-chair of the following international conferences: VI׳1998, VI׳2000, IWFHR׳2002, ICFHR׳2008, and ISSPA׳2012. He currently serves on the editorial board and is associate editor of several international journals: IJPRAI, IJDAR, and Pattern Recognition. He co-authored a book entitled, “Character Recognition Systems: A guide for Students and Practitioners,” John Wiley and Sons, Spring 2007. Dr. Cheriet was awarded the Queen Elizabeth II Diamond Jubilee Medal in light of his significant contributions to knowledge improvement in computational intelligence and mathematical modeling for image processing, created by MITCAS to mark the 60th anniversary of Her Majesty׳s accession to the throne. He holds NSERC Canada Research Chair Tier 1 in Sustainable Smart echo-Cloud. Dr. Cheriet is a senior member of the IEEE and the chapter founder and former chair of IEEE Montreal Computational Intelligent Systems (CIS).

Dr. Pierre-Marc Jodoin is a Canadian computer engineer and associate professor at the computer science department of the University of Sherbrooke, Canada. He got his Ph.D. with honour in computer vision and video analytics from the Université de Montréal in 2007. His research interests include video analytics and surveillance, image processing, medical imaging, and 3D reconstruction. He currently serves as an associate editor of the IEEE transactions on image processing journal and as an invited editor of the Pattern Recognition-Elsevier and Signal Processing-Elsevier journals. He is also director of the Sherbrooke Research center on smart environments which he co-founded in 2012. He also co-founded in 2010 the Sherbrooke medical image processing service, co-founded in 2011 Imeka.ca, a company specialized in medical imaging, and started the “changedetection.net” initiative in 2011, one of the significant benchmarking efforts in the field of video analytics.

Dr. Diane Beck received her Ph.D. in Psychology from the University of California, Berkeley. She was a postdoctoral fellow in Cognitive Neuroscience at University College London and then Princeton University. In 2005, she joined the Psychology Department at the University of Illinois, Urbana-Champaign. She is currently an Associate Professor of Psychology, a member of the Neuroscience Program, and the Group Leader of the Cognitive Neuroscience Group at the Beckman Institute for Advanced Science and Technology, at the University of Illinois. Her interests are in understanding the brain processes underlying visual perception and attention, including those involved in human change detection. She has used behavioural methods, functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) to study change detection and other visual processes in the human brain, as well as electroencephalography (EEG) and optical imaging to understand what neural processes give rise to visual awareness more generally. In addition she has applied pattern recognition techniques to fMRI data to investigate the visual cortex and its connectivity with other brain regions. Her publications include papers in premier journals and proceedings such as Nature Neuroscience, Proceedings of the National Academy of Sciences, Cerebral Cortex, Psychological Sciences, and Neural Information Processing Systems (NIPS).