UIC Code Recognition Using Computer Vision and LSTM Networks
UIC code is a key data for railway operations. This paper presents a method for UIC code recognition on locomotive and wagon. The approach is based on computer vision, to gain high-level understanding from digital images, and LSTM, a specific neural netwo
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in Computer and Information Science
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Dependable Computing EDCC 2020 Workshops AI4RAILS, DREAMS, DSOGRI, SERENE 2020 Munich, Germany, September 7, 2020 Proceedings
Communications in Computer and Information Science Commenced Publication in 2007 Founding and Former Series Editors: Simone Diniz Junqueira Barbosa, Phoebe Chen, Alfredo Cuzzocrea, Xiaoyong Du, Orhun Kara, Ting Liu, Krishna M. Sivalingam, Dominik Ślęzak, Takashi Washio, Xiaokang Yang, and Junsong Yuan
Editorial Board Members Joaquim Filipe Polytechnic Institute of Setúbal, Setúbal, Portugal Ashish Ghosh Indian Statistical Institute, Kolkata, India Igor Kotenko St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia Raquel Oliveira Prates Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Lizhu Zhou Tsinghua University, Beijing, China
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More information about this series at http://www.springer.com/series/7899
Simona Bernardi Valeria Vittorini Francesco Flammini Roberto Nardone Stefano Marrone Rasmus Adler Daniel Schneider Philipp Schleiß Nicola Nostro Rasmus Løvenstein Olsen Amleto Di Salle Paolo Masci (Eds.) •
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Dependable Computing EDCC 2020 Workshops AI4RAILS, DREAMS, DSOGRI, SERENE 2020 Munich, Germany, September 7, 2020 Proceedings
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Editors Simona Bernardi University of Zaragoza Zaragoza, Spain
Valeria Vittorini University of Naples Federico II Naples, Italy
Francesco Flammini Linnaeus University Växjö, Sweden
Roberto Nardone University of Reggio Calabria Reggio Calabria, Italy
Stefano Marrone University of Naples Federico II Naples, Italy
Rasmus Adler Fraunhofer IESE Kaiserslautern, Germany
Daniel Schneider Fraunhofer IESE Kaiserslautern, Germany
Philipp Schleiß Fraunhofer IKS Munich, Germany
Nicola Nostro Resiltech s.r.l. Pontedera, Italy
Rasmus Løvenstein Olsen Aalborg University Aalborg, Denmark
Amleto Di Salle University of L’Aquila L’Aquila, Italy
Paolo Masci National Institute of Aerospace, Langley Research Center Hampton, USA
ISSN 1865-0929 ISSN 1865-0937 (electronic) Communications in Computer and Information Science ISBN 978-3-030-58461-0 ISBN 978-3-030-58462-7 (eBook) https://doi.org/10.1007/978-3-030-58462-7 © 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 t
