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Neural Information Processing

27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18–22, 2020, Proceedings, Part V

  • Conference proceedings
  • © 2020

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Editors:
  1. Haiqin Yang

    1. Department of AI, Ping An Life, Shenzhen, China

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  2. Kitsuchart Pasupa

    1. Faculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

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  3. Andrew Chi-Sing Leung

    1. City University of Hong Kong, Kowloon, Hong Kong

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  4. James T. Kwok

    1. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, Hong Kong

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  5. Jonathan H. Chan

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

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  6. Irwin King

    1. The Chinese University of Hong Kong, New Territories, Hong Kong

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1333)

Included in the following conference series:

Conference proceedings info: ICONIP 2020.

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About this book

The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*

For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis.

* The conference was held virtually due to the COVID-19 pandemic.

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Table of contents (95 papers)

  1. Neural Network Models

    1. STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse

      • Sakshi Varshney, P. K. Srijith, Vineeth N. Balasubramanian
      Pages 676-684

    2. Variable-Depth Convolutional Neural Network for Text Classification

      • Ka-Hou Chan, Sio-Kei Im, Wei Ke
      Pages 685-692

  2. Robotics and Control

    1. Front Matter

      Pages 693-693
      Download chapter PDF

    2. Adaptive Neural Control for Efficient Rhythmic Movement Generation and Online Frequency Adaptation of a Compliant Robot Arm

      • Florentijn Degroote, Mathias Thor, Jevgeni Ignasov, Jørgen Christian Larsen, Emilia Motoasca, Poramate Manoonpong
      Pages 695-703

    3. An Ensemble Learning Approach to Improve Tracking Accuracy of Multi Sensor Fusion

      • Anoop Karnik Dasika, Praveen Paruchuri
      Pages 704-712

    4. Composition and Analysis of Pareto Optimal Compromise Solutions for Multiobjective Robust Controller Using GPC and CAN2s

      • Hironobu Nakayama, Ko Ogi, Kazuya Matsuo, Shuichi Kurogi
      Pages 713-722

    5. Part-Boundary-Aware Networks for Surgical Instrument Parsing

      • Jiaqi Liu, Yu Qiao, Jie Yang, Yun Gu
      Pages 723-730

  3. Time Series Analysis

    1. Front Matter

      Pages 731-731
      Download chapter PDF

    2. A Contextual Anomaly Detection Framework for Energy Smart Meter Data Stream

      • Xiufeng Liu, Zhichen Lai, Xin Wang, Lizhen Huang, Per Sieverts Nielsen
      Pages 733-742

    3. A New Time Series Forecasting Using Decomposition Method with SARIMAX Model

      • Chalermrat Nontapa, Chainarong Kesamoon, Nicha Kaewhawong, Peerasak Intrapaiboon
      Pages 743-751

    4. Adversarial Attacks on Deep Learning Systems for User Identification Based on Motion Sensors

      • Cezara Benegui, Radu Tudor Ionescu
      Pages 752-761

    5. An LSTM Based Deep Learning Method for Airline Ticket Price Prediction

      • Ke Du, Jiaxing Yan, Zhou Hang, Zhihao Chen, Lulu Wu
      Pages 762-769

    6. Attention-Based Multi-component LSTM for Internet Traffic Prediction

      • Qian Xu, Zhenjie Yao, Yanhui Tu, Yixin Chen
      Pages 770-777

    7. Entropy of LOO Predictable Horizons to Select a Learning Machine and a Representative Prediction of Chaotic Time Series

      • Daichi Miyazaki, Kazuya Matsuo, Shuichi Kurogi
      Pages 778-787

    8. Improving the Stability of a Convolutional Neural Network Time-Series Classifier Using SeLU and Tanh

      • Melanie Renkin, Jessica Sharmin Rahman
      Pages 788-795

    9. Proposing Two Different Feature Extraction Methods from Multi-fractal Detrended Fluctuation Analysis of Electroencephalography Signals: A Case Study on Attention-Deficit Hyperactivity Disorder

      • Zahra Roozbehi, Mahsa Mohaghegh, Hossein Lanjanian, Peyman Hassani Abharian
      Pages 796-803

    10. Recursive Maximum Correntropy Criterion Based Randomized Recurrent Broad Learning System

      • Yinuo Wang, Yu Guo, Fei Wang
      Pages 804-812

    11. Time and Incentive-Aware Neural Networks for Life Insurance Premium Prediction

      • Xinrui Li, Liang Zhao, Xi Yin, Yinxin Zhu, Jianping Shen, Wei Tong
      Pages 813-821

    12. To Augment or Not to Augment? Data Augmentation in User Identification Based on Motion Sensors

      • Cezara Benegui, Radu Tudor Ionescu
      Pages 822-831

    13. Unsupervised Visual Time-Series Representation Learning and Clustering

      • Gaurangi Anand, Richi Nayak
      Pages 832-840
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Other volumes

  1. Neural Information Processing

  2. Neural Information Processing

  3. Neural Information Processing

  4. Neural Information Processing

  5. Neural Information Processing

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

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