Springer Interdisciplinary Evolution of the Machine Brain: Vision, Touch & Mind (Research on Intelligent Manufacturing)

This book seeks to interpret connections between the machine brain, mind and vision in an alternative way and promote future research into the Interdisciplinary Evolution of Machine Brain (IEMB). It gathers novel research on IEMB, and offers readers a step-by-step introduction to the theory and algorithms involved, including data-driven approaches in machine learning, monitoring and understanding visual environments, using process-based perception to expand insights, mechanical manufacturing for remote sensing, reconciled connections between the machine brain, mind and vision, and the interdisciplinary evolution of machine intelligence. This book is intended for researchers, graduate students and engineers in the fields of robotics, Artificial Intelligence and brain science, as well as anyone who wishes to learn the core theory, principles, methods, algorithms, and applications of IEMB. From the Back Cover This book seeks to interpret connections between the machine brain, mind and vision in an alternative way and promote future research into the Interdisciplinary Evolution of Machine Brain (IEMB). It gathers novel research on IEMB, and offers readers a step-by-step introduction to the theory and algorithms involved, including data-driven approaches in machine learning, monitoring and understanding visual environments, using process-based perception to expand insights, mechanical manufacturing for remote sensing, reconciled connections between the machine brain, mind and vision, and the interdisciplinary evolution of machine intelligence. This book is intended for researchers, graduate students and engineers in the fields of robotics, Artificial Intelligence and brain science, as well as anyone who wishes to learn the core theory, principles, methods, algorithms, and applications of IEMB. About the Author Wenfeng Wang is a full professor in Shanghai Institute of Technology and the director of International Academy of Visual Art and Engineering. A key tallent in Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (2018- ). A reviewer of many SCI journals,including some top journals - Water Research, Science China-Information Sciences, Science of the Total Environment, Environmental Pollution, IEEE Transactions on Automation Science and Engineering and etc. A keynote speaker of AMICR2019, IACICE2020, OAES2020, AICS2021, 3DIT-MSP&DL2020 and etc. A scientist in chief of RealMax, Shanghai Lingang Artificial Intelligence Laboratory and etc.Hengjin Cai is currently a Full Professor and Ph.D. advisor at the School of Computer Science, Wuhan University, Hubei, China. His major research interests include economics, sociology, management and artificial intelligence. He also serves as the Executive Director of Zall Institute of Research, a Vice-President of China Communications Industry Association Professional Committee of Blockchain (CCIAPCB), a visiting researcher at the Center for Multimedia Technologies of Shenzhen Institutes of Advanced Technology, etc. He is a recipient of the 2017 Wu Wenjun Artificial Intelligence Science and Technology Award. Xiangyang Deng is currently a Full Professor (assistant) at the Institute of Information Fusion, Naval Aeronautical University, Yantai, China. His current research interests include video big data, deep learning and computational intelligence. Prof. Deng has extensive experience in R&D management. He has won three First Class Prizes and two Third Class Prizes for the Military Scientific and Technological Progress Award. He has published nine papers on related topics, five of which were indexed by SCI and EI.  Chenguang Lu is a retired teacher and a guest professor at the Institute of Intelligence Engineering and Mathematics, Liaoning Technical University, China. He used to be an associate professor at the department of information and computer science of Changsha University, China. He studied as a visit