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Langue: anglais
Edité par Springer Nature Singapore, 2023
ISBN 10 : 9811990050 ISBN 13 : 9789811990052
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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Chaocan Xiang is an Associate Professor at the College of Computer Science, Chongqing University, China. He received his bachelor¿s degree and Ph.D. from Nanjing Institute of Communication Engineering, China, in 2009 and 2014, respectively. He subsequently studied at the University of Michigan-Ann Arbor in 2017 (supervised by Prof. Kang G. Shin, IEEE Life Fellow, ACM Fellow). His research interests mainly include UAVs/vehicle-based crowdsensing, urban computing, Internet of Things, Artificial Intelligence, and big data. He has published more than 50 papers, including over 20 in leading venues such as IEEE Transactions on Mobile Computing, IEEE Transactions on Parallel and Distributed Systems, IEEE INFOCOM, and ACM Ubicomp. He has received a best paper award and a best poster award at two international conferences. Panlong Yang is a full Professor at the University of Science and Technology of China. He has been supported by the NSF Jiangsu through a Distinguished Young Scholarship and was honored as a CCF Distinguished Lecturer in 2015. He has published over 150 papers, including 40 in CCF Class A. Since 2012, he has supervised 14 master¿s and Ph.D. candidates, including two excellent dissertation winners in Jiangsu Province and the PLA education system. He has been supported by the National Key Development Project and NSFC projects. He has nominated by ACM MobiCom 2009 for the best demo honored mention awards, and won best paper awards at the IEEE MSN and MASS. He has served as general chair of BigCom and TPC chair of IEEE MSN. In addition, he has served as a TPC member of INFOCOM (CCF Class A) and an associate editor of the Journal of Communication of China. He is a Senior Member of the IEEE (2019). Fu Xiao received his Ph.D. in Computer Science and Technology from the Nanjing University of Science and Technology, Nanjing, China, in 2007. He is currently a Professor and Dean of the School of Computer, Nanjing University of Posts and Telecommunications. He has authored more than 60 papers in respected conference proceedings and journals, including IEEE INFOCOM, ACM Mobihoc, IEEE JASC, IEEE/ACM ToN, IEEE TPDS, IEEE TMC, etc. His main research interest is in the Internet of Things. He is a member of the IEEE Computer Society and the Association for Computing Machinery. Xiaochen Fan received his B.S. degree in Computer Science from Beijing Institute of Technology, Beijing, China, in 2013, and his Ph.D. from the University of Technology Sydney, NSW, Australia, in 2021. His research interests include mobile/pervasive computing, deep learning, and Internet of Things (IoT). He has published over 25 peer-reviewed papers in high-quality journals and IEEE/ACM international conference proceedings.
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Langue: anglais
Edité par Springer-Nature New York Inc, 2023
ISBN 10 : 9811990050 ISBN 13 : 9789811990052
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Ajouter au panierHardcover. Etat : Brand New. 214 pages. 9.25x6.10x9.21 inches. In Stock.
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Ajouter au panierHardcover. Etat : new. Hardcover. The purpose of this reprint is to provide readers with a comprehensive understanding of the latest advancements and technical approaches in the fields of remote sensing target detection and object detection. Remote sensing target detection focuses on identifying and locating specific targets of interest within remote sensing images, serving as a cornerstone for applications such as resource exploration, environmental monitoring, and national security. Recent years have witnessed significant progress in artificial intelligence (AI), which has been widely applied to tasks such as regression, clustering, and classification. While AI-driven methods exhibit remarkable capabilities in processing the vast volumes of data generated by remote sensing, they heavily rely on abundant high-quality labeled samples, posing challenges in the context of remote sensing big data. Consequently, their performance is often constrained by the scarcity of labeled data and the complexity of diverse backgrounds, making robust and practical target detection an ongoing challenge. This reprint gathers insights from leading experts, presenting cutting-edge research findings and offering forward-looking perspectives to address these pressing issues in remote sensing and object detection. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The purpose of this reprint is to provide readers with a comprehensive understanding of the latest advancements and technical approaches in the fields of remote sensing target detection and object detection. Remote sensing target detection focuses on identifying and locating specific targets of interest within remote sensing images, serving as a cornerstone for applications such as resource exploration, environmental monitoring, and national security. Recent years have witnessed significant progress in artificial intelligence (AI), which has been widely applied to tasks such as regression, clustering, and classification. While AI-driven methods exhibit remarkable capabilities in processing the vast volumes of data generated by remote sensing, they heavily rely on abundant high-quality labeled samples, posing challenges in the context of remote sensing big data. Consequently, their performance is often constrained by the scarcity of labeled data and the complexity of diverse backgrounds, making robust and practical target detection an ongoing challenge. This reprint gathers insights from leading experts, presenting cutting-edge research findings and offering forward-looking perspectives to address these pressing issues in remote sensing and object detection.
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Ajouter au panierBuch. Etat : Neu. Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection II | Buch | Englisch | 2025 | MDPI AG | EAN 9783725836055 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Langue: anglais
Edité par Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10 : 9811990050 ISBN 13 : 9789811990052
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Chaocan Xiang is an Associate Professor at the College of Computer Science, Chongqing University, China. He received his bachelor s degree and Ph.D. from Nanjing Institute of Communication Engineering, China, in 2009 and 2014, respectively. He subsequent.
Langue: anglais
Edité par Springer, Berlin|Springer Nature Singapore|Springer, 2024
ISBN 10 : 9811990085 ISBN 13 : 9789811990083
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Chaocan Xiang is an Associate Professor at the College of Computer Science, Chongqing University, China. He received his bachelor s degree and Ph.D. from Nanjing Institute of Communication Engineering, China, in 2009 and 2014, respectively. He subsequent.
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