Prof. Ruigang Yang, Head of Robotics and Auto-driving Lab, Baidu Research, China
Ruigang Yang is currently the chief scientist for 3D Vision at Baidu Research and leads the Robotics and Autonomous Driving Lab (RAL). Before joining Baidu, Dr. Yang was a full-time professor of computer science at the University of Kentucky. He obtained his PhD from the University of North Carolina at Chapel Hill and his MS degree from Columbia University. His research interests span computer graphics and computer vision, and he is particularly interested in 3D reconstruction and 3D data analysis. Dr. Yang has published over 100 papers, which, according to Google Scholar, have received close to 10,000 citations with an h-index of 48 (as of 2017). He has received a number of awards including the US NSF Career Award in 2004 and the Dean’s Research Award in 2013. Dr. Yang is currently an associate editor of IEEE TPAMI and a senior member of IEEE.
Prof. Ce ZHU, University of Electronic Science & Technology of China (IEEE Fellow)
Prof. Ce ZHU, University of Electronic Science & Technology of China
Ce Zhu is currently a Professor with the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China. His research interests include image/video coding and communications, video analysis and processing, 3D video, visual perception and applications. He has served on the editorial boards of a few journals, including as an Associate Editor of IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Broadcasting, and IEEE Signal Processing Letters. He has served on technical committees, organizing committees and as track/area/session chairs for over 60 international conferences, including serving as a Technical Program Co-Chair of IEEE ICME 2017. He is a Fellow of the IEEE and a Fellow of the IET. For more information, please visit his homepage at http://www.avc2-lab.net/~eczhu.
Speech Title: Towards Global Rate Distortion Optimization in Video Coding: Recent Developments
Abstract: The past decades have witnessed great advancement of video coding techniques and their wide applications in video storage and delivery, where rate-distortion optimization (RDO) plays a crucial role to maximize coding efficiency in video coding. In the current block-based hybrid video coding using motion compensation, the RDO is typically performed on the block level individually and independently, which is far from being optimal as it ignores the strong spatial-temporal dependency. However a global RDO problem becomes so complex that the processing of each coding unit is dependent and entangled each other due to the extensive use of spatial-temporal predictions in video coding. In the talk, I will discuss the challenges of achieving global RDO in one-pass video coding and present our recent work on temporally dependent RDO on top of the latest video coding standard HEVC.
Prof. Patrick Wang, Northeastern University, USA
Prof. Patrick S.P. Wang, PhD. Fellow, IAPR, ISIBM, WASE, IETI Distinguished Fellow and IEEE & ISIBM Outstanding Achievement Awardee, is Tenured Full Professor, Northeastern University, USA, iCORE (Informatics Circle of Research Excellence) Visiting Professor, Harvard, MIT, University of Calgary, Canada, Otto-Von-Guericke Distinguished Guest Professor, Magdeburg University, Germany, Zijiang Visiting Chair, ECNU, Shanghai, China, as well as honorary advisory professor of several key universities in China, including Sichuan University, Xiamen University, East China Normal University, Shanghai, and Guangxi Normal University, Guilin.
Prof. Wang received his BSEE from National Chiao Tung University (Jiaotong University), also known as China's MIT, MSEE from National Taiwan University, MSICS from Georgia Institute of Technology, and PhD, Computer Science from Oregon State University. Dr. Wang has published over 26 books, 200 technical papers, 3 USA/European Patents, in PR/AI/TV/Cybernetics/Imaging, and is currently founding Editor-in-Chief of IJPRAI (International Journal of Pattern Recognition and Artificial Intelligence) , and Book Series of MPAI, WSP. In addition to his technical interests, Dr. Wang also published a prose book, "Harvard Meditation Melody" 《哈佛冥想曲 》, 《劍橋狂想曲 》and many articles and poems regarding Du Fu and Li Bai's poems, Beethoven, Brahms, Mozart and Tchaikovsky's symphonies, and Bizet, Verdi, Puccini and Rossini's operas.
Speech Title: Intelligent Pattern Recognition (IPR) and Applications
Abstract: 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, 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.
Assoc. Prof. Yi Zhang, Sichuan University, China
YI ZHANG, Doctor, Associate Professor, he received the Ph.D. degree from the College of Computer Science, Sichuan University and he is currently an Associate Professor with the College of Computer Science, Sichuan University. From 2014 to 2015, he was with the Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA, as a Post-Doctoral Researcher. During his post-doctoral career, his teacher was Professor Ge Wang, an internationally renowned expert in CT imaging. He became a master supervisor and an Associate Professor in 2014.In 2018, he was promoted to a doctoral supervisor. Professor Zhang Yi has been engaged in medical physics and image inverse problems, including image reconstruction, sparse representation, deep learning and so on. He has authored about 40 papers in international academic journals, such as IEEE TMI，IEEE TCI，BOE，JOSA A，Neurocomputing. He has been invited to give presentations at several mainstream conferences in this field，such as IEEE NSS/MIC, IEEE ISBI, Fully 3D，SPIE Optics Engineering + Applications. He is in charge of many national and provincial projects, such as National Key R&D projects, National Natural Science Foundation of China, Sichuan Science and Technology Support Project, etc.
Speech Title: Deep Reconstruction: Deep Learning for CT Image Reconstruction
Abstract: In recent years, deep learning has achieved fruitful results in the field of computer vision and image processing, but in the field of medical imaging, its main application still remains in image analysis. This report mainly introduces some achievements and research progress in the field of image reconstruction based on deep learning, including low-dose image restoration based on residual self-encoder and sparse angle CT reconstruction evaluated by learning experts. Finally, the future development trend of deep learning for CT Image Reconstruction is prospected.