AI and Multimodal Services – AIMS 2024: 13th International Conference, Held as Part of the Services Conference...

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Xiuqin Pan Mengxing Huang

AI and Multimodal Services – AIMS 2024

13th International Conference, Held as Part of the Services Conference Federation, SCF 2024,...

Xiuqin Pan, Mengxing Huang, Jiajia Zhang , Junyang Chen

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English

Springer International Publishing AG
16 November 2024

Computer hardware; Artificial intelligence; Image processing

Series: Lecture Notes in Computer Science

This book constitutes the refereed proceedings of the 13th International Conference on AI and Multimodal Services – AIMS 2024, AIMS 2024, Held as Part of the Services Conference Federation, SCF 2024, held in Bangkok, Thailand, during November 16-19, 2024.

The 7 full papers and one short paper included in this book were carefully reviewed and selected from 16 submissions. They were organized in topical sections as follows: research track; application track; and short paper track.

Edited by: Xiuqin Pan, Mengxing Huang, Jiajia Zhang, Junyang Chen, Liang-Jie Zhang
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Volume: 15421
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783031776809
ISBN 10: 3031776801
Series: Lecture Notes in Computer Science
Pages: 113
Publication Date: 16 November 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

.- Research Track. .- A Paradigm Shift to Causal Model-Driven Decision-Making With Generative AI. .- Incorporating Feature Refinement Enhancement and Cross Network for Click-Through Rate Prediction. .- XcepSENet: An Intelligent Yoga Pose Classification System Based on Mediapipe. .- Arg-T5: A Multi-Perspective Argument Generation Method Based on Debate Topic. .- RCJE: A Machine Reading Comprehension Framework With Joint Coding for Emotion-Cause Pair Extraction. .- AI Value Protocol: Utilizing Blockchain to Promote AI. .- Application Track. .- Enhancing Customer Sentiment Analysis: A Hybrid Approach Using VADER and Machine Learning Techniques. .- Short Paper Track. .- Flood inundation range prediction method based on SRR-Informer.