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Produktbild: Advances and Trends in Artificial Intelligence. Theory and Applications
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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

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.07.2025

Abbildungen

XXIX, 534 p. 179 illus., 160 illus. in color.

Herausgeber

Hamido Fujita + weitere

Verlag

Springer Singapore

Seitenzahl

534

Maße (L/B/H)

23.5/15.5/3.1 cm

Gewicht

844 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9688-88-3

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.07.2025

Abbildungen

XXIX, 534 p. 179 illus., 160 illus. in color.

Herausgeber

Verlag

Springer Singapore

Seitenzahl

534

Maße (L/B/H)

23.5/15.5/3.1 cm

Gewicht

844 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9688-88-3

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Advances and Trends in Artificial Intelligence. Theory and Applications

  • .- 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.