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Human activity recognition and anomaly detection4th international workshop, DL-HAR 2024, and first international workshop, ADFM 2024, held in conjunction with IJCAI 2024 Jeju, South Korea, August 3-9, 2024, revised selected papers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Human activity recognition and anomaly detectionedited by Kuan-Chuan Peng ... [et al.].
Reminder of title:	4th international workshop, DL-HAR 2024, and first international workshop, ADFM 2024, held in conjunction with IJCAI 2024 Jeju, South Korea, August 3-9, 2024, revised selected papers /
other author:	Peng, Kuan-Chuan.
corporate name:
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xiv, 147 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Compilers (Computer programs)
Online resource:	https://doi.org/10.1007/978-981-97-9003-6
ISBN:	9789819790036$q(electronic bk.)

Human activity recognition and anomaly detection4th international workshop, DL-HAR 2024, and first international workshop, ADFM 2024, held in conjunction with IJCAI 2024 Jeju, South Korea, August 3-9, 2024, revised selected papers /
Human activity recognition and anomaly detection4th international workshop, DL-HAR 2024, and first international workshop, ADFM 2024, held in conjunction with IJCAI 2024 Jeju, South Korea, August 3-9, 2024, revised selected papers /[electronic resource] :edited by Kuan-Chuan Peng ... [et al.]. - Singapore :Springer Nature Singapore :2025. - xiv, 147 p. :ill., digital ;24 cm. - Communications in computer and information science,22011865-0937 ;. - Communications in computer and information science ;229..

-- Anomaly Detection with Foundation Models. -- GPT-4V-AD: Exploring Grounding Potential of VQA-oriented GPT-4V for Zero-shot Anomaly Detection. -- CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection. -- DDPM-MoCo: Advancing Industrial Surface Defect Generation and Detection with Generative and Contrastive Learning. -- Dual Memory-guided Probabilistic Model for Weakly-supervised Anomaly Detection. -- Deep Learning for Human Activity Recognition. -- Real-Time Human Action Prediction via Pose Kinematics. -- Uncertainty Awareness for Unsupervised Domain Adaptation on Human Activity Recognition. -- Deep Interaction Feature Fusion for Robust Human Activity Recognition. -- How effective are Self-Supervised models for Contact Identification in Videos. -- A Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition.

This book constitutes the refereed proceedings of the 4th International and First International Workshop on Human Activity Recognition and Anomaly Detection, Conjunction with IJCAI 2024, held in Jeju, South Korea, during August 3-9, 2024. The 9 full papers included in this book were carefully reviewed and selected from 14 submissions. They were organized in topical sections as follows: Anomaly Detection with Foundation Models and Deep Learning for Human Activity Recognition.

ISBN: 9789819790036$q(electronic bk.)

Standard No.: 10.1007/978-981-97-9003-6doiSubjects--Topical Terms:

1009141
Compilers (Computer programs)

LC Class. No.: Q334

Dewey Class. No.: 006.3

Human activity recognition and anomaly detection4th international workshop, DL-HAR 2024, and first international workshop, ADFM 2024, held in conjunction with IJCAI 2024 Jeju, South Korea, August 3-9, 2024, revised selected papers /
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505 0 $a -- Anomaly Detection with Foundation Models. -- GPT-4V-AD: Exploring Grounding Potential of VQA-oriented GPT-4V for Zero-shot Anomaly Detection. -- CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection. -- DDPM-MoCo: Advancing Industrial Surface Defect Generation and Detection with Generative and Contrastive Learning. -- Dual Memory-guided Probabilistic Model for Weakly-supervised Anomaly Detection. -- Deep Learning for Human Activity Recognition. -- Real-Time Human Action Prediction via Pose Kinematics. -- Uncertainty Awareness for Unsupervised Domain Adaptation on Human Activity Recognition. -- Deep Interaction Feature Fusion for Robust Human Activity Recognition. -- How effective are Self-Supervised models for Contact Identification in Videos. -- A Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition.
520 $a This book constitutes the refereed proceedings of the 4th International and First International Workshop on Human Activity Recognition and Anomaly Detection, Conjunction with IJCAI 2024, held in Jeju, South Korea, during August 3-9, 2024. The 9 full papers included in this book were carefully reviewed and selected from 14 submissions. They were organized in topical sections as follows: Anomaly Detection with Foundation Models and Deep Learning for Human Activity Recognition.
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