Professor Kuang-Chao Chou (also known as Guang-Zhao Zhou) is the former President of Chinese Academy of Sciences. He has been elected as the Academician of Chinese Academy of Sciences, Foreign Associate of the US National Academy of Sciences, Fellow of the Third World Academy of Science, Foreign Member of Soviet (Russian) Academy of Sciences, Czechoslovak Academy of Sciences, Bulgarian Academy of Sciences, Romania Academy of Sciences, Mongolian Academy of Sciences, the European Academy of Arts, Sciences and Humanities, Membre fondateur Academie Francophone d'Ingenieurs.He also served as the director of Institute of Theoretical Physics at the Chinese Academy of Sciences, the Dean of the Science School of Tsinghua University, the Chairman of the China Association for Sciences and Technology, the President of Pacific Science Association, Vice President of Third World Academy of Sciences.”Zhou is a first rate physicist: broad, powerful and very quick in grasping new ideas. His style of doing physics reminds me of that of Landau, Salam, and of Teller.”C N Yang”His published papers have won uniformly high praises by the international scientific community and his articles are always written with depth and elegance.”T D LeeThis volume presents a collection of selected papers written by Prof Chou. The papers are organized into four parts according to the subject of research areas and the language of publishing journals. Part I (in English) and Part III (in Chinese) are papers on field theories, particle physics and nuclear physics, Part II (in English) and Part IV (in Chinese) are papers on statistical physics and condensed matter physics. From the published papers, it illustrates and is clearly evident how Prof Chou was constantly at the frontiers of theoretical physics in various periods and carried out creative research works experimenting with initial ideas and motivations, as well as how he has driven and worked in different key research directions of theoretical physics, all for which he has made significant contributions to various interesting research areas and interdisciplinary fields.
The design of approximation algorithms for spanning tree problems has become an exciting and important area of theoretical computer science and also plays a significant role in emerging fields such as biological sequence alignments and evolutionary tree construction. While work in this field remains quite active, the time has come to collect under
Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image classification. As these technologies continue to advance, professionals have begun translating this intelligent programming language into mobile applications for devices. Programmers and web developers are in need of significant research on how to successfully develop pattern recognition applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities is an essential reference source that presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification, this book is ideally designed for programmers, developers, researchers, practitioners, engineers, academicians, students, scientists, and educators seeking coverage on the specific development of iOS mobile applications using pattern recognition strategies.
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.