Chomphuwiset / Kim / Pawara Multi-disciplinary Trends in Artificial Intelligence

14th International Conference, MIWAI 2021, Virtual Event, July 2–3, 2021, Proceedings
1. Auflage 2021
ISBN: 978-3-030-80253-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 189 Seiten, eBook

Reihe: Lecture Notes in Artificial Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Chomphuwiset, Phatthanaphong

Kim, Junmo

Pawara, Pornntiwa

Inhaltsverzeichnis

3D Point Cloud Upsampling and Colorization using GAN.- Learning Behavioral Rules from Multi-Agent Simulations for Optimizing Hospital Processes.- An Open-World Novelty Generator for Authoring Reinforcement Learning Environment of Standardized Toolkits.- Book Cover and Content Similarity Retrieval using Computer Vision and NLP Techniques.- Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers.- Feature Group Importance for Automated Essay Scoring.- Feature Extraction Efficient for Face Verification Based on Residual Network Architecture.- Acquiring Input Features from Stock Market Summaries: A NLG Perspective.- A Comparative of A New Hybrid based on Neural Networks and SARIMA Models for Time Series Forecasting.- Cartpole Problem with PDL and GP using Multi-Objective Fitness Functions Differing in A Priori Knowledge.- Learning Robot Arm Controls using Augmented Random Search in Simulated Environments.- An Analytical Evaluation of a Deep Learning Model to Detect Network Intrusion.- Application of Machine Learning Techniques to Predict Breast Cancer Survival.- Thai Handwritten Recognition on BEST2019 Datasets using Deep Learning.- Comparing of Multi-class Text Classification Methods for Automatic Ratings of Consumer Reviews.- Designing An Algorithm for Scheduling Tasks for Multiagent Systems.