Zhenghua Chen - Generalization with Deep Learning: For Improvement on Sensing Capability

Editors

Zhenghua Chen Min Wu Xiaoli Li

Institute for Infocomm Research, Singapore

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World Scientific Publishing Co. Pte. Ltd.

5 Toh Tuck Link, Singapore 596224

USA office:27 Warren Street, Suite 401-402, Hackensack, NJ 07601

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Library of Congress Cataloging-in-Publication Data

Names: Chen, Zhenghua, editor. | Wu, Min, 1974 editor. | Li, Xiao-Li, 1969 editor.

Title: Generalization with deep learning : for improvement on sensing capability / editors, Zhenghua Chen, Min Wu, Xiaoli Li, Institute for Infocomm Research, Singapore.

Description: Singapore ; Hackensack, NJ : World Scientific, [2021] | Includes bibliographical references and index.

Identifiers: LCCN 2020034548 | ISBN 9789811218835 (hardcover) | ISBN 9789811218842 (ebook) | ISBN 9789811218859 (ebook other)

Subjects: LCSH: Electronic surveillance--Data processing. | Remote sensing--Data processing. | Diagnostic imaging--Data processing. | Machine learning.

Classification: LCC TK7882.E2 G44 2021 | DDC 006.3/1--dc23

LC record available at https://lccn.loc.gov/2020034548

British Library Cataloguing-in-Publication Data

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https://doi.org/10.1142/9789811218842_fmatter

Zhenghua Chenreceived his B.Eng. degree from University of Electronic Science and Technology of China in 2011, and Ph.D. degree from Nanyang Technological University (NTU), Singapore in 2017. He has been working at NTU as a Research Fellow. Currently, he is a Scientist and Team Leader at Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore as well as part-time Lecturer at NTU. He works as PI and Co-PI for several large projects (> S$10 million). He serves as Guest Editor for four journals, Track Chairs for two conferences, Organizer for two workshops at International Joint Conference on Artificial Intelligence (IJCAI) 2019 and 2020, one invited session at IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV) 2020 and one special session at IEEE International Conference on Industrial Engineering and Applications (ICIEA) 2021, and PC member for several top AI conferences, such as IJCAI and Association for the Advancement of Artificial Intelligence (AAAI). His Google Scholar citation is 2000+ with an H-index of 18. He has been listed as Worlds Top 2% Scientists by researchers from Stanford University. Besides, he has won several competitive awards such as the A*STAR Career Development Award, First Runner-Up Award for Grand Challenge at IEEE VCIP 2020, Finalist Academic Paper Award of IEEE ICPHM 2020, and Chinese Government Award for Outstanding Self-financed Students Abroad.