Evaluation of Deep Learning Accelerators for Object Detection at the Edge
Deep learning is moving more and more from the cloud towards the edge. Therefore, embedded devices are needed that are reasonably cheap, energy-efficient and fast enough. In this paper we evaluate the performance and energy consumption of popular, off-the
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Ute Schmid Franziska Klügl Diedrich Wolter (Eds.)
KI 2020: Advances in Artificial Intelligence 43rd German Conference on AI Bamberg, Germany, September 21–25, 2020 Proceedings
123
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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More information about this series at http://www.springer.com/series/1244
Ute Schmid Franziska Klügl Diedrich Wolter (Eds.) •
•
KI 2020: Advances in Artificial Intelligence 43rd German Conference on AI Bamberg, Germany, September 21–25, 2020 Proceedings
123
Editors Ute Schmid Universität Bamberg Bamberg, Germany
Franziska Klügl Örebro University Örebro, Sweden
Diedrich Wolter Universität Bamberg Bamberg, Germany
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-58284-5 ISBN 978-3-030-58285-2 (eBook) https://doi.org/10.1007/978-3-030-58285-2 LNCS Sublibrary: SL7 – Artificial Intelligence © 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 regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
This proceedings volume contains the papers presented at the 43rd German Conference on Artificial Intelligence (KI 2020), held during September 21–25, 2020, hosted by University of Bamberg, Germany. Due to COVID-19, KI 2020 was the first virtual edition of this conference series. The German conference on Artificial Intelligence (abbreviated KI for “Künstliche Intelligenz”) has developed from a series of unofficial meetings and w
