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Neural Information Processing

27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part III

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12534)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Conference series link(s): ICONIP: International Conference on Neural Information Processing

Conference proceedings info: ICONIP 2020.

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Table of contents (52 papers)

  1. Front Matter

    Pages i-xxv
  2. Biomedical Information

    1. Front Matter

      Pages 1-1
    2. Classification of Neuroblastoma Histopathological Images Using Machine Learning

      • Adhish Panta, Matloob Khushi, Usman Naseem, Paul Kennedy, Daniel Catchpoole
      Pages 3-14
    3. Data Mining ENCODE Data Predicts a Significant Role of SINA3 in Human Liver Cancer

      • Matloob Khushi, Usman Naseem, Jonathan Du, Anis Khan, Simon K. Poon
      Pages 15-25
    4. Diabetic Retinopathy Detection Using Multi-layer Neural Networks and Split Attention with Focal Loss

      • Usman Naseem, Matloob Khushi, Shah Khalid Khan, Nazar Waheed, Adnan Mir, Atika Qazi et al.
      Pages 26-37
    5. Enhancer-DSNet: A Supervisedly Prepared Enriched Sequence Representation for the Identification of Enhancers and Their Strength

      • Muhammad Nabeel Asim, Muhammad Ali Ibrahim, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
      Pages 38-48
    6. Machine Learned Pulse Transit Time (MLPTT) Measurements from Photoplethysmography

      • Philip Mehrgardt, Matloob Khushi, Anusha Withana, Simon Poon
      Pages 49-62
    7. Weight Aware Feature Enriched Biomedical Lexical Answer Type Prediction

      • Keqin Peng, Wenge Rong, Chen Li, Jiahao Hu, Zhang Xiong
      Pages 63-75
  3. Neural Data Analysis

    1. Front Matter

      Pages 77-77
    2. Decoding Olfactory Cognition: EEG Functional Modularity Analysis Reveals Differences in Perception of Positively-Valenced Stimuli

      • Nida Itrat Abbasi, Sony Saint-Auret, Junji Hamano, Anumita Chaudhury, Anastasios Bezerianos, Nitish V. Thakor et al.
      Pages 79-89
    3. Inter and Intra Individual Variations of Cortical Functional Boundaries Depending on Brain States

      • Zhen Zhang, Junhai Xu, Luqi Cheng, Cheng Chen, Lingzhong Fan
      Pages 98-109
    4. Phase Synchronization Indices for Classification of Action Intention Understanding Based on EEG Signals

      • Xingliang Xiong, Xuesong Lu, Lingyun Gu, Hongfang Han, Zhongxian Hong, Haixian Wang
      Pages 110-121
    5. The Evaluation of Brain Age Prediction by Different Functional Brain Network Construction Methods

      • Hongfang Han, Xingliang Xiong, Jianfeng Yan, Haixian Wang, Mengting Wei
      Pages 122-134
    6. Transfer Dataset in Image Segmentation Use Case

      • Anna Wróblewska, Sylwia Sysko-Romańczuk, Karol Prusinowski
      Pages 135-146
  4. Neural Network Models

    1. Front Matter

      Pages 147-147
    2. A Gaussian Process-Based Incremental Neural Network for Online Regression

      • Xiaoyu Wang, Lucian Gheorghe, Jun-ichi Imura
      Pages 149-161
    3. Are Deep Neural Architectures Losing Information? Invertibility is Indispensable

      • Yang Liu, Zhenyue Qin, Saeed Anwar, Sabrina Caldwell, Tom Gedeon
      Pages 172-184
    4. Automatic Dropout for Deep Neural Networks

      • Veena Dodballapur, Rajanish Calisa, Yang Song, Weidong Cai
      Pages 185-196

About this book

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually.
The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.

Editors and Affiliations

  • Department of AI, Ping An Life, Shenzhen, China

    Haiqin Yang

  • Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Kitsuchart Pasupa

  • City University of Hong Kong, Kowloon, Hong Kong

    Andrew Chi-Sing Leung

  • Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, Hong Kong

    James T. Kwok

  • School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Jonathan H. Chan

  • The Chinese University of Hong Kong, New Territories, Hong Kong

    Irwin King

Bibliographic Information

  • Book Title: Neural Information Processing

  • Book Subtitle: 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part III

  • Editors: Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-63836-8

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2020

  • Softcover ISBN: 978-3-030-63835-1Published: 19 November 2020

  • eBook ISBN: 978-3-030-63836-8Published: 18 November 2020

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXV, 643

  • Number of Illustrations: 36 b/w illustrations, 190 illustrations in colour

  • Topics: Pattern Recognition, Machine Learning, Database Management, Computer Appl. in Social and Behavioral Sciences

Buy it now

Buying options

Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access