Collection
Engineering: Neural Computing Technologies for Applied Sciences
Currently, neural computing technologies have moved toward data-centric applications due to the development of large memory capacity, fast processing speed and data computation. With the growing demand of applied sciences, advanced neural computing technologies are needed to process the data generated in practical applications. To promote the development of neural computing and related technologies, this Topical Collection will provide a platform for researchers to exchange the latest research and practitioner findings. The collection will concentrate on the hot topics of neural computing. This special section aims to achieve the deep integration of computer science, electronic engineering, communication engineering, and applied mathematics. The Topical Collection is expected to accelerate the development of neural computing technologies and the adoption for applied science applications.
Topics of interest in this Topical Collection include (but are not limited to):
(1) deep learning-driven computer vision, pattern recognition and industrial applications
(2) computational intelligence methods and their engineering applications
(3) machine learning methods for data-driven applied sciences
(4) neural computing-based intelligent systems for applied sciences
Editors
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Xin Zhang
Dr Xin Zhang, Tianjin Normal University, China. He is an Associate Professor of College of Artificial Intelligence in Tianjin Normal University. His research interests are wireless networks, artificial intelligence, resource allocation. He has published more than forty papers in international journals and conferences.
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Yang Lou
Dr Yang Lou, National Yang Ming Chiao Tung University, China. He is an Assistant Professor with the Department of Computer Science, National Yang Ming Chiao Tung University. His research interests include network science, machine learning, graph learning, and evolutionary computation. He has published more than thirty papers in international journals and conferences.
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Weizhi Meng
Dr Weizhi Meng, Technical University of Denmark, Denmark. He is an Assistant Professor in Department of Applied Mathematics and Computer Science, Technical University of Denmark. His research interests are cyber security and intelligent technology in security, smartphone security, biometric authentication. He served as program committee members for 20+ international conferences. He is co-PC chair for IEEE Blockchain 2018, IEEE ATC 2019, IFIPTM 2019, Socialsec 2019. He also served as guest editor for FGCS, JISA, Sensors, CAEE, IJDSN, SCN, WCMC, etc.
