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Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning

28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II

  • Igor V. Tetko
  • Věra Kůrková
  • Pavel Karpov
  • Fabian Theis
Conference proceedings ICANN 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11728)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 11728)

Table of contents

  1. Front Matter
    Pages i-xxx
  2. Feature Selection

    1. Front Matter
      Pages 1-1
    2. Sijia Niu, Pengfei Zhu, Qinghua Hu, Hong Shi
      Pages 3-15
    3. Tirtharaj Dash, Ashwin Srinivasan, Ramprasad S. Joshi, A. Baskar
      Pages 29-45
    4. Yang Fan, Jianhua Dai, Qilai Zhang, Shuai Liu
      Pages 46-58
    5. Alexandra Degeest, Michel Verleysen, Benoît Frénay
      Pages 59-71
    6. Vadim Borisov, Johannes Haug, Gjergji Kasneci
      Pages 72-83
    7. Nicomedes L. Cavalcanti Jr., Marcelo Rodrigo Portela Ferreira, Francisco de Assis Tenorio de Carvalho
      Pages 84-95
  3. Augmentation Techniques

    1. Front Matter
      Pages 101-101
    2. Yuuji Ichisugi, Naoto Takahashi, Hidemoto Nakada, Takashi Sano
      Pages 103-114
    3. Ricardo Cruz, Joaquim F. Pinto Costa, Jaime S. Cardoso
      Pages 115-124
    4. Shizheng Qin, Kangzheng Gu, Lecheng Wang, Lizhe Qi, Wenqiang Zhang
      Pages 125-137
    5. Guanghua Tan, Zijun Guo, Yi Xiao
      Pages 138-149
  4. Weights Initialization

    1. Front Matter
      Pages 151-151
    2. Bernhard Bermeitinger, Tomas Hrycej, Siegfried Handschuh
      Pages 153-164
    3. Aiga Suzuki, Hidenori Sakanashi
      Pages 165-169
    4. Diego Aguirre, Olac Fuentes
      Pages 170-184
  5. Parameters Optimisation

    1. Front Matter
      Pages 185-185
    2. Enzo Tartaglione, Daniele Perlo, Marco Grangetto
      Pages 187-200
    3. Serdar Iplikci, Batuhan Bilgi, Ali Menemen, Bedri Bahtiyar
      Pages 201-207
    4. Konstantin Berestizshevsky, Guy Even
      Pages 208-219
    5. Anders Sjöberg, Magnus Önnheim, Emil Gustavsson, Mats Jirstrand
      Pages 220-231
    6. Sebastian Bock, Martin Weiß
      Pages 232-243
  6. Pruning Networks

    1. Front Matter
      Pages 245-245
    2. Yun Li, Luyang Wang, Sifan Peng, Aakash Kumar, Baoqun Yin
      Pages 263-274
    3. Tinghuai Wang, Lixin Fan, Huiling Wang
      Pages 275-287
    4. Niange Yu, Cornelius Weber, Xiaolin Hu
      Pages 288-298
    5. Chuanguang Yang, Zhulin An, Chao Li, Boyu Diao, Yongjun Xu
      Pages 299-305
    6. Junxing Hu, Ling Li, Yijun Lin, Fengge Wu, Junsuo Zhao
      Pages 321-333
    7. Yuan Liu, Xi Jia, Linlin Shen, Zhong Ming, Jinming Duan
      Pages 334-346
  7. Search for an Optimal Architecture

    1. Front Matter
      Pages 347-347
    2. Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev
      Pages 349-360
    3. Alexey Alexeev, Yuriy Matveev, Anton Matveev, Dmitry Pavlenko
      Pages 361-372
    4. Aftab Anjum, Fengyang Sun, Lin Wang, Jeff Orchard
      Pages 373-386
    5. Sebastian Litzinger, Andreas Klos, Wolfram Schiffmann
      Pages 387-392
  8. Confidence Estimation

  9. Continual Learning

    1. Front Matter
      Pages 451-451
    2. Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
      Pages 466-480
    3. Christian Limberg, Kathrin Krieger, Heiko Wersing, Helge Ritter
      Pages 495-506
    4. Rudolf Szadkowski, Jan Drchal, Jan Faigl
      Pages 507-517

Other volumes

  1. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part I
  2. Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning
    28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II
  3. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part III
  4. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part IV
  5. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings

About these proceedings

Introduction

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. 

The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. 

Keywords

artificial intelligence classification clustering computational linguistics computer networks Human-Computer Interaction (HCI) image processing image reconstruction image segmentation imaging systems learning algorithms machine learning neural networks recurrent neural networks robotics semantics sensors signal processing Support Vector Machines (SVM) user interfaces

Editors and affiliations

  1. 1.Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)NeuherbergGermany
  2. 2.Institute of Computer ScienceCzech Academy of SciencesPrague 8Czech Republic
  3. 3.Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)NeuherbergGermany
  4. 4.Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)NeuherbergGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-30484-3
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-30483-6
  • Online ISBN 978-3-030-30484-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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