{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":22,"n_cols":5,"rows_kept":22,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[10,2,10,3],[16,2,16,3],[17,2,17,3],[19,2,19,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910983029903321"]
[null,null,"Autore",null,"Peng Kuan-Chuan"]
[null,null,"Titolo",null,"Human Activity Recognition and Anomaly Detection : 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 / / edited by Kuan-Chuan Peng, Yizhou Wang, Ziyue Li, Zhenghua Chen, Jianfei Yang, Sungho Suh, Min Wu"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9789819790036"]
[{"$nulls":4},"9789819790029"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (156 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 2201"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Compilers (Computer programs)"]
[{"$nulls":4},"Computer simulation"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Compilers and Interpreters"]
[{"$nulls":4},"Computer Modelling"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- 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."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 4th International "]
[{"$nulls":4},"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."]