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001480758 001__ 1480758
001480758 003__ OCoLC
001480758 005__ 20231031003307.0
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001480758 020__ $$a9789819958344
001480758 020__ $$a9819958342
001480758 020__ $$z9789819958337
001480758 0247_ $$a10.1007/978-981-99-5834-4$$2doi
001480758 035__ $$aSP(OCoLC)1396696074
001480758 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE
001480758 049__ $$aISEA
001480758 050_4 $$aQ334
001480758 08204 $$a006.3$$223/eng/20230912
001480758 1112_ $$aAsian Conference on Intelligent Information and Database Systems$$n(15th :$$d2023 :$$cPhuket, Thailand)
001480758 24510 $$aIntelligent information and database systems :$$b15th Asian Conference, ACIIDS 2023, Phuket, Thailand, July 24-26, 2023, proceedings.$$nPart I /$$cNgoc Thanh Nguyen, Siridech Boonsang, Hamido Fujita, Bogumiła Hnatkowska, Tzung-Pei Hong, Kitsuchart Pasupa, Ali Selamat, editors.
001480758 24630 $$aACIIDS 2023
001480758 260__ $$aSingapore :$$bSpringer,$$c2023.
001480758 300__ $$a1 online resource (xxvii, 449 pages) :$$billustrations (chiefly color).
001480758 4901_ $$aLecture notes in computer science. Lecture notes in artificial intelligence ;$$v13995
001480758 4901_ $$aLNCS sublibrary: SL7 - Artificial intelligence
001480758 500__ $$aDescription based upon print version of record.
001480758 5058_ $$aIntro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Case-Based Reasoning and Machine Comprehension -- On the Improvement of the Reasoning Cycle in Case-Based Reasoning -- 1 Introduction -- 2 A More Domain Knowledge Independent Approach -- 2.1 Case Structure -- 2.2 Retrieving Similar Cases -- 2.3 An Optimization Approach for Adaptation -- 3 Experimental Evaluation -- 3.1 Case Study -- 3.2 Dataset Description -- 3.3 Testbed Setup -- 3.4 Empirical Evaluation -- 4 Conclusion -- References
001480758 5058_ $$aExploring Incompleteness in Case-Based Reasoning: A Strategy for Overcoming Challenge -- 1 Introduction -- 2 Background -- 2.1 Case-Based Reasoning and Data Completeness -- 2.2 Change Point Analysis -- 3 The Completeness Challenge: A Problem Statement -- 3.1 Illustrative Scenario -- 3.2 Problem Formulation -- 4 Evaluating Data Incompleteness in CBR Systems -- 4.1 Segmentation of the Case Base -- 4.2 Identification of Incompleteness Situations -- 5 Experimental Results -- 6 Conclusion -- References -- Leveraging both Successes and Failures in Case-Based Reasoning for Optimal Solutions
001480758 5058_ $$a1 Introduction -- 2 Illustrative Example and Preliminary Concepts -- 2.1 Key Concepts and Notations Related to the CBR Paradigm -- 2.2 Collision Avoidance Navigation -- 3 Adaptation Through Failed and Successful Cases -- 3.1 Problem Statement -- 3.2 Principle -- 3.3 Local Prediction of the Target Solution -- 4 Evaluation -- 4.1 Experimental Design -- 4.2 Baselines and Metrics -- 4.3 Results -- 5 Conclusion -- References -- Transfer Learning for Abnormal Behaviors Identification in Examination Room from Surveillance Videos: A Case Study in Vietnam*-1pc -- 1 Introduction -- 2 Related Work
001480758 5058_ $$a3 Methods -- 3.1 Abnormal Behaviors in the Examination Hall and Data Collection -- 3.2 Deep Learning Architectures for Abnormal Behavior Detection -- 4 Experimental Results -- 4.1 Environmental Settings -- 4.2 Abnormal Behavior Detection Using YOLO V4 -- 4.3 Abnormal Behavior Detection with SSD MobileNet V2 -- 4.4 Discussion -- 5 Conclusion -- References -- A Novel Question-Context Interaction Method for Machine Reading Comprehension -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Sentence Embedding -- 3.2 S-QCI Block -- 3.3 Word Fusion: -- 3.4 Training Process -- 4 Experiment
001480758 5058_ $$a4.1 Experimental Setup -- 4.2 Benchmark Dataset and Baseline Models -- 4.3 Main Results -- 4.4 Ablation Study -- 5 Conclusion -- References -- Granular Computing to Forecast Alzheimer's Disease Distinctive Individual Development -- 1 Introduction -- 2 Methods -- 2.1 Rough Set Implementation of GrC -- 3 Results -- 3.1 Statistics -- 3.2 Granular Computing for Reference of Group1 Group -- 3.3 Granular Computing for Reference of Group2 Patients -- 4 Discussion -- References -- Computer Vision -- AdVLO: Region Selection via Attention-Driven for Visual LiDAR Odometry -- 1 Introduction -- 2 Related Works
001480758 506__ $$aAccess limited to authorized users.
001480758 520__ $$aThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 2426, 2023. The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.
001480758 650_0 $$aArtificial intelligence$$vCongresses.$$xMedical applications$$0(DLC)sh 88003000
001480758 650_0 $$aDatabase management$$vCongresses.$$vCongresses$$0(DLC)sh2008102037
001480758 655_7 $$aConference papers and proceedings.$$2lcgft
001480758 655_0 $$aElectronic books.
001480758 7001_ $$aNguyen, Ngoc Thanh$$c(Computer scientist),$$eeditor.$$c(Computer scientist)$$0(Uk)007172842
001480758 7001_ $$aBoonsang, Siridech,$$eeditor.
001480758 7001_ $$aFujita, Hamido,$$eeditor.
001480758 7001_ $$aHnatkowska, Bogumiła,$$eeditor.
001480758 7001_ $$aHong, Tzung-Pei,$$d1963-$$eeditor.
001480758 7001_ $$aPasupa, Kitsuchart,$$eeditor.
001480758 7001_ $$aSelamat, Ali,$$eeditor.
001480758 77608 $$iPrint version:$$aNguyen, Ngoc Thanh$$tIntelligent Information and Database Systems$$dSingapore : Springer,c2023$$z9789819958337
001480758 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001480758 830_0 $$aLecture notes in computer science ;$$v13995.
001480758 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001480758 852__ $$bebk
001480758 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5834-4$$zOnline Access$$91397441.1
001480758 909CO $$ooai:library.usi.edu:1480758$$pGLOBAL_SET
001480758 980__ $$aBIB
001480758 980__ $$aEBOOK
001480758 982__ $$aEbook
001480758 983__ $$aOnline
001480758 994__ $$a92$$bISE