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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 I

  • Conference proceedings
  • © 2022

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, Teesside 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 13529)

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.

Chapter “Sim-to-Real Neural Learning with Domain Randomisation for Humanoid Robot Grasping ” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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Keywords

Table of contents (63 papers)

  1. Front Matter

    Pages i-xxii
    Download chapter PDF

  2. A Novel Deep Learning Based Method for Doppler Spectral Curve Detection

    • Keming Mao, Yitao Ren, Liancheng Yin, Yan Jin
    Pages 1-12

  3. A Unified Multiple Inducible Co-attentions and Edge Guidance Network for Co-saliency Detection

    • Zhenshan Tan, Xiaodong Gu
    Pages 13-24

  4. Attention Guided Network for Salient Object Detection in Optical Remote Sensing Images

    • Yuhan Lin, Han Sun, Ningzhong Liu, Yetong Bian, Jun Cen, Huiyu Zhou
    Pages 25-36

  5. BiSMSM: A Hybrid MLP-Based Model of Global Self-Attention Processes for EEG-Based Emotion Recognition

    • Wei Li, Ye Tian, Bowen Hou, Jianzhang Dong, Shitong Shao
    Pages 37-48

  6. Boosting Both Robustness and Hardware Efficiency via Random Pruning Mask Selection

    • Ruixin Xue, Meiqi Wang, Zhongfeng Wang
    Pages 49-60

  7. Brain Tumor Segmentation Framework Based on Edge Cloud Cooperation and Deep Learning

    • Saifeng Feng, Jianhui Zhao, Wenyuan Zhao, Tingbao Zhang
    Pages 61-72

  8. CLTS+: A New Chinese Long Text Summarization Dataset with Abstractive Summaries

    • Xiaojun Liu, Shunan Zang, Chuang Zhang, Xiaojun Chen, Yangyang Ding
    Pages 73-84

  9. Correlation-Based Transformer Tracking

    • Minghan Zhong, Fanglin Chen, Jun Xu, Guangming Lu
    Pages 85-96

  10. Deep Graph and Sequence Representation Learning for Drug Response Prediction

    • Xiangfeng Yan, Yong Liu, Wei Zhang
    Pages 97-108

  11. DOT-VAE: Disentangling One Factor at a Time

    • Vaishnavi Patil, Matthew Evanusa, Joseph JaJa
    Pages 109-120

  12. DuSAG: An Anomaly Detection Method in Dynamic Graph Based on Dual Self-attention

    • Weiqin Lin, Xianyu Bao, Mark Junjie Li, Zukang Gao
    Pages 121-132

  13. Exploring Deep Learning Architectures for Localised Hourly Air Quality Prediction

    • Sooraj Raj, Jim Smith, Enda Hayes
    Pages 133-144

  14. Face Super-Resolution with Spatial Attention Guided by Multiscale Receptive-Field Features

    • Weikang Huang, Shiyong Lan, Wenwu Wang, Xuedong Yuan, Hongyu Yang, Piaoyang Li et al.
    Pages 145-157

  15. F-Measure Optimization for Multi-class, Imbalanced Emotion Classification Tasks

    • Toki Tahmid Inan, Mingrui Liu, Amarda Shehu
    Pages 158-170

  16. F-Transformer: Point Cloud Fusion Transformer for Cooperative 3D Object Detection

    • Jie Wang, Guiyang Luo, Quan Yuan, Jinglin Li
    Pages 171-182

  17. How to Face Unseen Defects? UDGAN for Improving Unseen Defects Recognition

    • Yaxi Chen, Ruimin Hu, Zheng Wang, Yuke Li
    Pages 183-194

  18. Learning to Generate Textual Adversarial Examples

    • Xiangzhe Guo, Shikui Tu, Lei Xu
    Pages 195-206

  19. Lymphoma Ultrasound Image Segmentation with Self-Attention Mechanism and Stable Learning

    • Yingkang Han, Dehua Chen, Yishu Luo, Yijie Dong
    Pages 207-218

  20. MetaAudio: A Few-Shot Audio Classification Benchmark

    • Calum Heggan, Sam Budgett, Timothy Hospedales, Mehrdad Yaghoobi
    Pages 219-230
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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, Teesside University, Middlesbrough, UK

    Chrisina Jayne

  • Democritus University of Thrace, Xanthi, Greece

    Antonios Papaleonidas

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

    Mehmet Aydin

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