Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives

As the size of multimedia databases grows, retrieval becomes a key challenge in multimedia database management. Accordingly, it is necessary to apply machine learning techniques to automatically tune the mechanism of multimedia retrieval systems. Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives disseminates current information on multimedia retrieval, advances the field of multimedia databases, and educates the multimedia database community. It is a critical text for professionals who are engaged in efforts to understand machine learning techniques for adaptive multimedia retrieval research, design and applications.

Chia-Hung Wei is currently an assistant professor of the Department of Information Management at Ching Yun University, Taiwan. He obtained his Ph.D. degree in Computer Science from the University of Warwick, UK, and Master's degree from the University of Sheffield, UK, and Bachelor degree from the Tunghai University, Taiwan. His research interests include content-based image retrieval, digital image processing, medical image processing and analysis, machine learning for multimedia applications and information retrieval. He has published over 10 research papers in those research areas.

Yue Li received his Ph.D. degree in computer science from University of Warwick, UK, in 2009, M.S. in Information Technology from Department of Computer Science, University of Nottingham, UK, in 2005, and B.Sc. in Mathematics from Nankai University, China, in 2003. He is currently an assistant professor of Collage of Software, University of Nankai, China. He serves as a member of editorial review board of International Journal of Digital Crime and Forensics. His research interests include digital forensics, multimedia security, digital watermarking, pattern recognition, machine learning and content-based image retrieval.