Advances and Trends in Artificial Intelligence. Theory and Applications : 38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2025, Kitakyushu, Japan, July 1–4, 2025, Proceedings, Part I / / edited by Hamido Fujita, Yutaka Watanobe, Moonis Ali, Yinglin Wang

• Autore: Fujita Hamido
• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026
• Edizione: 1st ed. 2026.
• Descrizione fisica: 1 online resource (811 pages)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Artificial Intelligence
• Altri autori: WatanobeYutaka AliMoonis WangYinglin
• Nota di contenuto: -- Reinforcement Learning. -- An Enhanced Preference-Based Reinforcement Learning Framework for Autonomous System. -- Reinforcement Learning based Iterated Greedy for Parallel Machine Scheduling with Weighted Earliness Tardiness. -- VMD-IMF Enhanced Hyper Graph Attention Module Based Reinforcement Learning For Portfolio Optimization. -- A reinforcement learning based framework to the facility layout problem. -- Optimization. -- Bayesian Optimization for Fine-Tuning an AI Solver: Application to Preventive Maintenance Scheduling Problems. -- Domain Generalization through Domain-Expert Risk Assessment. -- Enhanced Optimization Space Learning: Towards Real-Time Compiler Optimization. -- Optimizing Feature Selection Binary Peacock Algorithm with improved movement strategy. -- Natural Language Processing. -- Apply TF-IDF and LDA to Explore Topics and Related Trends in Electric Vehicle Reviews. -- Identifying Fake Reviews and Their Implications Using BERT and LDA: A Case Study of Online Shopping Website Reviews. -- A Lightweight and Efficient Punctuation and Word Casing Prediction Model for On Device Streaming ASR. -- SYNCAD: Synchronised Yields from Narrative Cross Modal Audio and Data. -- MultiGAU: Real Time Sign Language Generation using Multimodal Gated Attention. -- Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI. -- Multi-Agent. -- Hierarchical Multi-Agent Reinforcement Learning with Epistemic Priors for Scalable Communicationless Coordination of Teamable Agents. -- DynaMIX: Sample-Efficient Multi Agent Reinforcement Learning with Multi-Step Temporal Forward Dynamics Modeling. -- Automated Issue Hierarchy Generation for Improved Automated Negotiation Outcomes. -- Machine Learning and Decision Making. -- Distribution Variance for Surrogate Weights in Multi-Criteria Decision Analysis. -- Bridging the Trust Gap: Leveraging Explainable AI for Personalized E-Commerce Recommendations. -- A clustering method based on hesitant difference granularity. -- Evaluation of Efficient AI for the Edge: Insights from Deep Neural Networks Model Compression Techniques Applied to Occupancy Detection. -- LSTM-based Proactive Scheduling of Stream Applications in Edge/Cloud Environments. -- Uncertainty Quantification Of Multimodal Models. -- Knowledge Representation. -- Automating OntoClean Ontology Verification. -- Automating OntoClean - Subsumption Hierarchy Construction. -- Possibilistic Reasoning with Fuzzy Formal Contexts: An Extended Abstract. -- A Strategy for Implementing Garbage Detection in Ontology Completion using Description Logics. -- Data Engineering. -- Uncertainty-based Instance-Dependent Noisy Label Datasets Generation. -- Guided by Uncertainty: Semi-supervised Domain Adaptation with Curriculum and Contrastive Learning. -- Linking Data Meaningfully: Identifying Meaningful Keys and Foreign Keys from Data. -- CAMI: A missing value imputation method based on causal discovery and self-attention. -- MDR: An Ontology Vocabulary and Registry Service for Dataset Catalogs. -- A-REACT: Adaptive Resampling and Active Classification for Thresholded Anomalies. -- DistResampleR-Lite: Light Distributed Resampler for Imbalanced Regression Problems. -- Fast HSIC-based tests for random processes. -- Large Language Model. -- Exploring the Efficacy of Large Language Models in Predicting Chemical Toxicity. -- Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT LLM in Chaotic Environments. -- LLM-base MaSE, A Software Development Framework for Developing Multi-Agent Systems. -- Computer Vision. -- WeldViT: A Lightweight Network for Online Identification of Multi-Label Welding Defects. -- Impact of Replay Ratios on Performance and Efficiency in Continual Learning for Skeleton-based Action Recognition. -- Extending YOLO for Feature-Based Classification Through Numerical-to-Image Transformation. -- Lost in the Noise: Evading and Detecting Backdoors in Conditional Diffusion Models. . SkinPalNet: An Advanced Ensemble Model for Skin Cancer Diagnosis with Computer Vision Approach. -- Enhancing Minimarket Customer Experience through YOLOv8-Powered Checkout Systems. -- Brain Tumor MRI Interpretation: Towards a Benchmark for Medical Visual Question Answering.
• Sommario/riassunto: This book constitutes the refereed proceedings of the 38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems on Advances and Trends in Artificial Intelligence, IEA/AIE 2025, held in Kitakyushu, Japan, in July 1–4, 2025. The 80 full papers and 9 short papers included in this book were carefully reviewed and selected from 130 submissions. They focus on the following topical sections: Part I: Reinforcement Learning; Optimization; Natural Language Processing; Multi-Agent; Machine Learning and Decision Making; Knowledge Representation; Data Engineering; Large Language Model; Computer Vision. Part II: Robotics; Education; Cyber Security; Healthcare and Medical Applications; Advanced Applied Intelligence Methodologies and Applications; Intelligent Systems and e-Applications; Industrial and Engineering Applications.
• Titolo autorizzato: Advances and Trends in Artificial Intelligence. Theory and Applications
• ISBN: 981-9688-89-2
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911047809003321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 15706