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Neural Information Processing

30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part III

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Biao Luo

    1. Central South University, Changsha, China

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  2. Long Cheng

    1. Chinese Academy of Sciences, Beijing, China

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  3. Zheng-Guang Wu

    1. Zhejiang University, Hangzhou, China

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  4. Hongyi Li

    1. Guangdong University of Technology, Guangzhou, China

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  5. Chaojie Li

    1. UNSW Sydney, Sydney, Australia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14449)

Included in the following conference series:

Conference proceedings info: ICONIP 2023.

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About this book

The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. 


The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. 


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Table of contents (45 papers)

  1. Front Matter

    Pages i-xxi
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  2. Theory and Algorithms

    1. Front Matter

      Pages 1-1
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    2. Efficient Lightweight Network with Transformer-Based Distillation for Micro-crack Detection of Solar Cells

      • Xiangying Xie, Xinyue Liu, QiXiang Chen, Biao Leng
      Pages 3-15

    3. MTLAN: Multi-Task Learning and Auxiliary Network for Enhanced Sentence Embedding

      • Gang Liu, Tongli Wang, Wenli Yang, Zhizheng Yan, Kai Zhan
      Pages 16-27

    4. Correlated Online k-Nearest Neighbors Regressor Chain for Online Multi-output Regression

      • Zipeng Wu, Chu Kiong Loo, Kitsuchart Pasupa
      Pages 28-39

    5. Evolutionary Computation for Berth Allocation Problems: A Survey

      • Xin-Xin Xu, Yi Jiang, Lei Zhang, Xun Liu, Xiang-Qian Ding, Zhi-Hui Zhan
      Pages 40-51

  3. Cognitive Neurosciences

    1. Front Matter

      Pages 53-53
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    2. Privacy-Preserving Travel Time Prediction for Internet of Vehicles: A Crowdsensing and Federated Learning Approach

      • Hongyu Huang, Cui Sun, Xinyu Lei, Nankun Mu, Chunqiang Hu, Chao Chen et al.
      Pages 55-66

    3. A Fine-Grained Domain Adaptation Method for Cross-Session Vigilance Estimation in SSVEP-Based BCI

      • Kangning Wang, Shuang Qiu, Wei Wei, Ying Gao, Huiguang He, Minpeng Xu et al.
      Pages 67-80

    4. RMPE:Reducing Residual Membrane Potential Error for Enabling High-Accuracy and Ultra-low-latency Spiking Neural Networks

      • Yunhua Chen, Zhimin Xiong, Ren Feng, Pinghua Chen, Jinsheng Xiao
      Pages 81-93

    5. An Improved Target Searching and Imaging Method for CSAR

      • Yuxiao Deng, Chuandong Li, Yawei Shi, Huiwei Wang, Huaqing Li
      Pages 94-106

    6. Block-Matching Multi-pedestrian Tracking

      • Chao Zhang
      Pages 107-124

    7. RPF3D: Range-Pillar Feature Deep Fusion 3D Detector for Autonomous Driving

      • Yihan Wang, Qiao Yan
      Pages 125-146

    8. Traffic Signal Control Optimization Based on Deep Reinforcement Learning with Attention Mechanisms

      • Wenlong Ni, Peng Wang, Zehong Li, Chuanzhuang Li
      Pages 147-158

    9. CMCI: A Robust Multimodal Fusion Method for Spiking Neural Networks

      • Runhao Jiang, Jianing Han, Yingying Xue, Ping Wang, Huajin Tang
      Pages 159-171

    10. A Weakly Supervised Deep Learning Model for Alzheimer’s Disease Prognosis Using MRI and Incomplete Labels

      • Zhi Chen, Yongguo Liu, Yun Zhang, Jiajing Zhu, Qiaoqin Li
      Pages 172-185

    11. Two-Stream Spectral-Temporal Denoising Network for End-to-End Robust EEG-Based Emotion Recognition

      • Xuan-Hao Liu, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu
      Pages 186-197

    12. Brain-Inspired Binaural Sound Source Localization Method Based on Liquid State Machine

      • Yuan Li, Jingyue Zhao, Xun Xiao, Renzhi Chen, Lei Wang
      Pages 198-213

    13. A Causality-Based Interpretable Cognitive Diagnosis Model

      • Jinwei Zhou, Zhengyang Wu, Changzhe Yuan, Lizhang Zeng
      Pages 214-226

    14. RoBrain: Towards Robust Brain-to-Image Reconstruction via Cross-Domain Contrastive Learning

      • Che Liu, Changde Du, Huiguang He
      Pages 227-238
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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

  6. Neural Information Processing

  7. Neural Information Processing

  8. Neural Information Processing

  9. Neural Information Processing

  10. Neural Information Processing

  11. Neural Information Processing

  12. Neural Information Processing

  13. Neural Information Processing

  14. Neural Information Processing

  15. Neural Information Processing

Editors and Affiliations

  • Central South University, Changsha, China

    Biao Luo

  • Chinese Academy of Sciences, Beijing, China

    Long Cheng

  • Zhejiang University, Hangzhou, China

    Zheng-Guang Wu

  • Guangdong University of Technology, Guangzhou, China

    Hongyi Li

  • UNSW Sydney, Sydney, Australia

    Chaojie Li

Bibliographic Information

  • Book Title: Neural Information Processing

  • Book Subtitle: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part III

  • Editors: Biao Luo, Long Cheng, Zheng-Guang Wu, Hongyi Li, Chaojie Li

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-981-99-8067-3

  • Publisher: Springer Singapore

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024

  • Softcover ISBN: 978-981-99-8066-6Published: 16 November 2023

  • eBook ISBN: 978-981-99-8067-3Published: 15 November 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXI, 617

  • Number of Illustrations: 26 b/w illustrations, 186 illustrations in colour

  • Topics: Pattern Recognition, Data Mining and Knowledge Discovery, Machine Learning, Computer Applications

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