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Multi-disciplinary Trends in Artificial Intelligence

14th International Conference, MIWAI 2021, Virtual Event, July 2–3, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Phatthanaphong Chomphuwiset

    1. Mahasarakham University, Maha Sarakham, Thailand

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  2. Junmo Kim

    1. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

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    You can also search for this editor in PubMed   Google Scholar

  3. Pornntiwa Pawara

    1. Mahasarakham University, Maha Sarakham, Thailand

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12832)

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

Included in the following conference series:

Conference proceedings info: MIWAI 2021.

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About this book

This book constitutes the refereed proceedings of the 14th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2021, held online in July 2021.

The 13 full papers and 3 short papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of topics in theory, methods, and tools in AI sub-areas such as cognitive science, computational philosophy, computational intelligence, game theory, machine learning, multi-agent systems, natural language, representation and reasoning, data mining, speech, computer vision and the Web as well as their applications in big data, bioinformatics, biometrics, decision support, knowledge management, privacy, recommender systems, security, software engineering, spam filtering, surveillance, telecommunications, Web services, and IoT.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. 3D Point Cloud Upsampling and Colorization Using GAN

    • Beomyoung Kim, Sangeun Han, Eojindl Yi, Junmo Kim
    Pages 1-13

  3. Learning Behavioral Rules from Multi-Agent Simulations for Optimizing Hospital Processes

    • Daan Apeldoorn, Lars Hadidi, Torsten Panholzer
    Pages 14-26

  4. An Open-World Novelty Generator for Authoring Reinforcement Learning Environment of Standardized Toolkits

    • Sangho Lee, Junbeom Park, Ho Suk, Taewoo Kim, Pamul Yadav, Shiho Kim
    Pages 27-33

  5. Book Cover and Content Similarity Retrieval Using Computer Vision and NLP Techniques

    • Chatklaw Jareanpon, Khanabhorn Kawattikul
    Pages 34-44

  6. Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers

    • Stefanie Krause, Oliver Otto, Frieder Stolzenburg
    Pages 45-57

  7. Feature Group Importance for Automated Essay Scoring

    • Jih Soong Tan, Ian K. T. Tan
    Pages 58-70

  8. Feature Extraction Efficient for Face Verification Based on Residual Network Architecture

    • Thananchai Khamket, Olarik Surinta
    Pages 71-80

  9. Acquiring Input Features from Stock Market Summaries: A NLG Perspective

    • Aristotle Tan, Hui-Ngo Goh, Lai-Kuan Wong
    Pages 81-93

  10. A Comparative of a New Hybrid Based on Neural Networks and SARIMA Models for Time Series Forecasting

    • Chalermrat Nontapa, Chainarong Kesamoon, Nicha Kaewhawong, Peerasak Intrapaiboon
    Pages 94-105

  11. Cartpole Problem with PDL and GP Using Multi-objective Fitness Functions Differing in a Priori Knowledge

    • Peter David Shannon, Chrystopher L. Nehaniv, Somnuk Phon-Amnuaisuk
    Pages 106-117

  12. Learning Robot Arm Controls Using Augmented Random Search in Simulated Environments

    • Somnuk Phon-Amnuaisuk, Peter David Shannon, Saiful Omar
    Pages 118-128

  13. An Analytical Evaluation of a Deep Learning Model to Detect Network Intrusion

    • Md Al-Imran, Kazi Jahidur Rahaman, Mohammad Rasel, Shamim H. Ripon
    Pages 129-140

  14. Application of Machine Learning Techniques to Predict Breast Cancer Survival

    • Jaree Thomgkam, Vatinee Sukmak, Papidchaya Klangnok
    Pages 141-151

  15. Thai Handwritten Recognition on BEST2019 Datasets Using Deep Learning

    • Rapeeporn Chamchong, Umaporn Saisangchan, Pornntiwa Pawara
    Pages 152-163

  16. Comparing of Multi-class Text Classification Methods for Automatic Ratings of Consumer Reviews

    • Jantima Polpinij, Bancha Luaphol
    Pages 164-175

  17. Improving Safety and Efficiency for Navigation in Multiagent Systems

    • Chattrakul Sombattheera
    Pages 176-187

  18. Correction to: Thai Handwritten Recognition on BEST2019 Datasets Using Deep Learning

    • Rapeeporn Chamchong, Umaporn Saisangchan, Pornntiwa Pawara
    Pages C1-C1

  19. Back Matter

    Pages 189-189
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Other volumes

  1. Multi-disciplinary Trends in Artificial Intelligence

Editors and Affiliations

  • Mahasarakham University, Maha Sarakham, Thailand

    Phatthanaphong Chomphuwiset, Pornntiwa Pawara

  • Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Junmo Kim

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