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Artificial Neural Networks and Machine Learning – ICANN 2022

31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV

  • Conference proceedings
  • © 2022

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Overview

Editors:
  1. Elias Pimenidis

    1. University of the West of England, Bristol, UK

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  2. Plamen Angelov

    1. Lancaster University, Lancaster, UK

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  3. Chrisina Jayne

    1. Digital Innovation, Teeside University, Middlesbrough, UK

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  4. Antonios Papaleonidas

    1. Democritus University of Thrace, Xanthi, Greece

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  5. Mehmet Aydin

    1. The University of the West of England, Bristol, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13532)

Included in the following conference series:

Conference proceedings info: ICANN 2022.

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About this book

The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022.
The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications.

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Keywords

Table of contents (65 papers)

  1. Loop Closure Detection Based on Siamese ConvNet Features and Geometrical Verification for Visual SLAM

    • Zhe Chen, Xiaofeng Zhang, Yaojun Ou, Mei Wang
    Pages 719-730
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  2. Multi-Sensor Data Fusion for Short-Term Traffic Flow Prediction: A Novel Multi-Channel Data Structure Integrated with Mixed-Pointwise Convolution and Channel Attention Mechanism

    • Ruijun Feng, Mingzhou Chen
    Pages 731-742
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  3. Neural Architecture Search for Low-Precision Neural Networks

    • Binyi Wu, Bernd Waschneck, Christian Mayr
    Pages 743-755
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  4. RegionDrop: Fast Human Pose Estimation Using Annotation-Aware Spatial Sparsity

    • Youki Sada, Seiya Shibata, Yuki Kobayashi, Takashi Takenaka
    Pages 756-768
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  5. SDCN: A Species-Disease Hybrid Convolutional Neural Network for Plant Disease Recognition

    • Yiqi Yang
    Pages 769-780
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  6. TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation

    • Zihan Li, Dihan Li, Cangbai Xu, Weice Wang, Qingqi Hong, Qingde Li et al.
    Pages 781-792
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  7. Back Matter

    Pages 793-795
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Other volumes

  1. Artificial Neural Networks and Machine Learning – ICANN 2022

  2. Artificial Neural Networks and Machine Learning – ICANN 2022

  3. Artificial Neural Networks and Machine Learning – ICANN 2022

  4. Artificial Neural Networks and Machine Learning – ICANN 2022

Editors and Affiliations

  • University of the West of England, Bristol, UK

    Elias Pimenidis

  • Lancaster University, Lancaster, UK

    Plamen Angelov

  • Digital Innovation, Teeside University, Middlesbrough, UK

    Chrisina Jayne

  • Democritus University of Thrace, Xanthi, Greece

    Antonios Papaleonidas

  • The University of the West of England, Bristol, UK

    Mehmet Aydin

Bibliographic Information

  • Book Title: Artificial Neural Networks and Machine Learning – ICANN 2022

  • Book Subtitle: 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV

  • Editors: Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-15937-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Softcover ISBN: 978-3-031-15936-7Published: 07 September 2022

  • eBook ISBN: 978-3-031-15937-4Published: 06 September 2022

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXII, 795

  • Number of Illustrations: 21 b/w illustrations, 259 illustrations in colour

  • Topics: Artificial Intelligence, Computer Applications, Image Processing and Computer Vision, Information Systems and Communication Service

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