Broad-Classifier for Remote Sensing Scene Classification with Spatial and Channel-Wise Attention
Remote sensing scene classification is an important technology, which is widely used in military and civil applications. However, it is still a challenging problem due to the complexity of scene images. Recently, the development of remote sensing satellit
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Nadia Magnenat-Thalmann · Constantine Stephanidis · Enhua Wu · Daniel Thalmann · Bin Sheng · Jinman Kim · George Papagiannakis · Marina Gavrilova (Eds.)
Advances in Computer Graphics 37th Computer Graphics International Conference, CGI 2020 Geneva, Switzerland, October 20–23, 2020 Proceedings
Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA
Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA
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Nadia Magnenat-Thalmann Constantine Stephanidis Enhua Wu Daniel Thalmann Bin Sheng Jinman Kim George Papagiannakis Marina Gavrilova (Eds.) •
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Advances in Computer Graphics 37th Computer Graphics International Conference, CGI 2020 Geneva, Switzerland, October 20–23, 2020 Proceedings
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Editors Nadia Magnenat-Thalmann University of Geneva Geneva, Switzerland
Constantine Stephanidis University of Crete Heraklion, Greece
Enhua Wu University of Macau Macau, China
Daniel Thalmann Swiss Federal Institute of Technology Lausanne, Switzerland
Bin Sheng Shanghai Jiao Tong University Shanghai, China
Jinman Kim University of Sydney Sydney, Australia
George Papagiannakis University of Crete Heraklion, Greece
Marina Gavrilova University of Calgary Calgary, AB, Canada
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-61863-6 ISBN 978-3-030-61864-3 (eBook) https://doi.org/10.1007/978-3-030-61864-3 LNCS Sublibrary: SL6 – Image Processing, Computer Vision, Pattern Recognition, and Graphics © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with