Chu / Shuai / Shen | Technologies and Applications of Artificial Intelligence | Buch | 978-981-964588-6 | sack.de

Buch, Englisch, 358 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 569 g

Reihe: Communications in Computer and Information Science

Chu / Shuai / Shen

Technologies and Applications of Artificial Intelligence

29th International Conference, TAAI 2024, Hsinchu, Taiwan, December 6-7, 2024, Proceedings, Part I
Erscheinungsjahr 2025
ISBN: 978-981-964588-6
Verlag: Springer Nature Singapore

29th International Conference, TAAI 2024, Hsinchu, Taiwan, December 6-7, 2024, Proceedings, Part I

Buch, Englisch, 358 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 569 g

Reihe: Communications in Computer and Information Science

ISBN: 978-981-964588-6
Verlag: Springer Nature Singapore


This two-volume set CCIS 2414 and CCIS 2415 constitutes the refereed proceedings of the 29th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2024 held in Hsinchu, Taiwan, during December 6–7, 2024.

The 49 full papers presented in these two volumes were carefully reviewed and selected from 147 submissions.

The papers are organized in the following topical sections:

Part I: Data Robustness; Image Analysis; Knowledge Representation and Management; Games; Machine Learning and Applications; AI Studies; JSAI Special Session 1.

Part II: JSAI Special Session 2; Japan Special Session 3; International Track Special Session.

Chu / Shuai / Shen Technologies and Applications of Artificial Intelligence jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


.- Data Robustness.
.- A Study on Synthesizing Expressive Violin Performances: Approaches and Comparisons.
.- Towards User Autonomy in Electricity Market by Evaluating Incentive Sufficiency for Demand Response Participation.
.- Graph-Based Syntactic Analysis for Cross-Domain Fraud Messages Detection.
.- Image Analysis.
.- Dynamically searching and classifying images by using neural networks and reinforcement learning with the grid table.
.- MLDN-Net: Multi-level denoising neural network for wet fingerprint via cyclic multivariate function.
.- Training-free Zero-shot Composed Image Retrieval via Weighted Modality Fusion and Similarity.
.- Uncertainty-Error correlations in Evidential Deep Learning Models for Biomedical Segmentation.
.- Knowledge Representation and Management.
.- Causality-Driven Patent Valuation: Integrating Domain Knowledge and Language Models in a Structured Interview-Like Selection Process.
.- Rationale-Driven Predictions for Stock Movements: A Multi-Model Integration and Stack Generalization Approach.
.- An Adaptive Sample Selection Approach for Learning with Noisy Labels.
.- Games.
.- R-CoT: Reinforcement Chain of Thought Prompting for Task Specific Training.
.- A Lookup Table for Deficiency Number Calculation in Mahjong.
.- Player Models of Go Historical Master Figures.
.- Machine Learning and Applications.
.- An Intrusion Detection System for Heterogeneous OT- enabled Networks Using Hybrid Deep Learning Mode.
.- Ranking Comments for Bug Reports using Deep Learning.
.- Hand Gesture Recognition from sEMG Signals through Quantum Support Vector Machine.
.- AI Studies.
.- Enhancing Literature Reviews in Human-Machine Collaboration: A Comparative Analysis of Topic Modeling Methods in Computer Science.
.- Metal Price Prediction by Encoding Daily Insights of Sparse Macroeconomic Factors and Integrating Dynamic Asset Correlations.
.- Smart lighting control built on AI architecture.
.- Predicting 24-Hour Emergency Room Revisits: A Concept Bottleneck Approach.
.- JSAI Special Session 1.
.- Proposal on Dashboard Generation Support Using Knowledge Graphs and Association Rules.
.- Synthetic Data Generation for Book Recommendation Using Knowledge Graph Embedding.
.- Proposal on Dashboard Creation for Understanding Users from Rating Matrix.
.- Estimation of Confidence Level Based on Eye Movement and Temporal Self-Evaluations Using CNN with Data Augmentation.
.- Persuasion Process from the Perspective of Decision-Making Model in Werewolf Games.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.