• The Course
• The Lecturers
• School venue
• Travel and accomodation
• Open projects
• Final tests

Download:

• Application form 2020
• Application for Scholarships 2020

 

• Course Schedule 2019 - PDF
• Course Schedule 2018 - PDF
• Course Schedule 2017 - PDF
• Course Schedule 2016 - PDF
• Course Schedule 2015 - PDF

   

• Student presentations 2019 - PDF

Prof. Harry Wechsler

Harry Wechsler received the PhD degree in computer science from the University of California, Irvine, in 1975. Currently, he is a professor of computer science and director for the Center of Distributed and Intelligent Computation at George Mason University (GMU). His research in the field of intelligent systems focuses on active learning, biometrics, computational vision, data mining, data streaming, image and signal processing, machine learning and pattern recognition, and statistical learning theory using transduction and semi-supervised learning. The range of applications covers among others biometrics for data fusion, face recognition, gait analysis, performance evaluation and error analysis; learning for anomaly, change, intrusion, and outlier detection; HCI; and video processing and surveillance. He has published more than 250 scientific papers, serves on the editorial board of major scientific publications, and is the author of Computational Vision (Academic Press, 1990). He organized and directed the NATO Advanced Study Institute (ASI) on “Face Recognition: From Theory to Applications” (Stirling, UK, 1997), and was the principal co – editor for its seminal proceedings published by Springer (1998). His book on Reliable Face Recognition Methods, which breaks new ground in applied modern pattern recognition and biometrics, was published by Springer in 2007. Dr. Wechsler directed at GMU the design and development of FERET, which has become the standard facial data base used for benchmark studies and experimentation. He was elected an IEEE Fellow in 1992 for “contributions to spatial/spectral image representations and neural networks and their theoretical integration and application to human and machine perception” and an IAPR (International Association of Pattern Recognition) Fellow in 1998. His doctoral students upon graduation have assumed important positions in academia, government, and industry. He was granted (together with his former doctoral students) three patents by US Patent Office (USPO) on fractal image compression using quad-q-learning (licensed in 2006), on feature based classification (for face recognition), and on open set recognition using transduction. Three additional patents, (1) on data stream change detector, (2) on adaptive and robust correlation filters (for robust recognition), and (3) on selective (co)training from labeled and unlabeled exemplars, have been filed with USPO and are now pending.