PRICAI 2024: Trends in Artificial Intelligence: 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, Kyoto, Japan, November 18–24, 2024, Proceedings, Part I | SpringerLink
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PRICAI 2024: Trends in Artificial Intelligence

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, Kyoto, Japan, November 18–24, 2024, Proceedings, Part I

  • Conference proceedings
  • © 2025

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Editors:
  1. Rafik Hadfi

    1. Kyoto University, Kyoto, Japan

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  2. Patricia Anthony

    1. Lincoln University, Christchurch, New Zealand

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  3. Alok Sharma

    1. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

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  4. Takayuki Ito

    1. Kyoto University, Kyoto, Japan

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  5. Quan Bai

    1. University of Tasmania, Tasmania, Australia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 15281)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: PRICAI 2024.

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About this book

The five-volume proceedings set LNAI 15281-15285, constitutes the refereed proceedings of the 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, held in Kyoto, Japan, in November 18–24, 2024.

The 145 full papers and 35 short papers included in this book were carefully reviewed and selected from 543 submissions. 

The papers are organized in the following topical sections:

Part I: Machine Learning, Deep Learning

Part II: Deep Learning, Federated Learning, Generative AI, Natural Language Processing, Large Language Models, 

Part III: Large Language Models, Computer Vision

Part IV: Computer Vision, Autonomous Driving, Agents and Multiagent Systems, Knowledge Graphs, Speech Processing, Optimization

Part V: Optimization, General Applications, Medical Applications, Theoretical Foundations of AI

Keywords

Table of contents (40 papers)

  1. Front Matter

    Pages i-xxiv
    Download chapter PDF

  2. Machine Learning

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Quantitative Analysis of Training Methods, Data Size, and User-Specific Effectiveness in DL-Based Personalized Aesthetic Evaluation

      • Yoshia Abe, Tatsuya Daikoku, Yasuo Kuniyoshi
      Pages 3-15

    3. EQUISCALE: Equitable Scaling for Abstention Learning

      • Tejas Chaudhari, Naresh Manwani
      Pages 16-28

    4. Unsupervised Clustering Using a Variational Autoencoder with Constrained Mixtures for Posterior and Prior

      • Mashfiqul Huq Chowdhury, Yuichi Hirose, Stephen Marsland, Yuan Yao
      Pages 29-40

    5. UTBoost: Gradient Boosted Decision Trees for Uplift Modeling

      • Junjie Gao, Xiangyu Zheng, DongDong Wang, Zhixiang Huang, Bangqi Zheng
      Pages 41-53

    6. CodeMosaic Patch: Physical Adversarial Attacks Against Infrared Aerial Object Detectors

      • Hangwei He, Libing Wu, Enshu Wang, Yizhou Wang, Yu Zhao
      Pages 54-68

    7. Sequential Clustering for Real-World Datasets

      • Chongwei Huang, Jian Hou, Huaqiang Yuan
      Pages 69-80

    8. Dual-Mode Contrastive Learning-Enhanced Knowledge Tracing

      • Danni Huang, Jicheng Yu, Shun Mao, Jiawei Li, Yuncheng Jiang
      Pages 81-92

    9. Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks

      • Zhibo Jin, Jiayu Zhang, Zhiyu Zhu, Xinyi Wang, Yiyun Huang, Huaming Chen
      Pages 93-105

    10. Characterization of Similarity Metrics in Epistemic Logic

      • Xiaolong Liang, Yì N. Wáng
      Pages 106-118

    11. A Relaxed Symmetric Non-negative Matrix Factorization Approach for Community Discovery

      • Zhigang Liu, Hao Yan, Yurong Zhong, Weiling Li
      Pages 119-133

    12. Enhanced Cognitive Distortions Detection and Classification Through Data Augmentation Techniques

      • Mohamad Rasmy, Caroline Sabty, Nourhan Sakr, Alia El Bolock
      Pages 134-145

    13. Enhancing Music Genre Classification Using Augmented Features Ensemble Learning Technique

      • Raad Shariat, John Z. Zhang
      Pages 146-157

    14. A Multi-layer Network Community Detection Method via Network Feature Augmentation and Contrastive Learning

      • Min Teng, Chao Gao, Zhen Wang, Tanimoto Jun
      Pages 158-169

    15. Scene Text Recognition Based on Corner Point and Attention Mechanism

      • Hui Wang, Tao Hu, Xiaoke Geng, Kai Li
      Pages 170-181

    16. A Comprehensive Framework for Debiased Sample Selection Across All Noise Types

      • Naihao Wang, Ruirui Li
      Pages 182-193

    17. A Traffic Flow Prediction Model Integrating Dynamic Implicit Graph Information

      • You Wu, Jingfeng Guo, Xiao Chen, Xiao Pan, Bin Liu
      Pages 194-208

    18. A Recursive Learning Algorithm for the Least Squares SVM

      • Xiao-Lei Xia, Mingxing Ouyang
      Pages 209-220

    19. BDEL: A Backdoor Attack Defense Method Based on Ensemble Learning

      • Zhihuan Xing, Yuqing Lan, Yin Yu, Yong Cao, Xiaoyi Yang, Yichun Yu et al.
      Pages 221-235
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Other volumes

  1. PRICAI 2024: Trends in Artificial Intelligence

  2. PRICAI 2024: Trends in Artificial Intelligence

  3. PRICAI 2024: Trends in Artificial Intelligence

  4. PRICAI 2024: Trends in Artificial Intelligence

  5. PRICAI 2024: Trends in Artificial Intelligence

Editors and Affiliations

  • Kyoto University, Kyoto, Japan

    Rafik Hadfi, Takayuki Ito

  • Lincoln University, Christchurch, New Zealand

    Patricia Anthony

  • RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Alok Sharma

  • University of Tasmania, Tasmania, Australia

    Quan Bai

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