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Database and Expert Systems Applications - DEXA 2025 Workshops - AISys and AI4IP, Bangkok, Thailand, August 25-27, 2025, Proceedings

Englisch · Taschenbuch

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This volume constitutes the refereed proceedings of the 7th International Workshop on AI System Engineering: Math, Modelling and Software, AISys 2025 and the First International Workshop on Optimisation of Industrial Production with AI Algorithms, AI4IP, co-located with the 36th International Conference on Database and Expert Systems Applications, DEXA 2025, which took place in Bangkok, Thailand, during August 25-27, 2025.
The 11 full papers were thoroughly reviewed and selected from a total of 23 submissions. They are organized in topical sections as follows: AI System Engineering: Math, Modelling and Software; and Optimization of Industrial Production with AI Algorithms.

Inhaltsverzeichnis

.- AI System Engineering: Math, Modelling and Software.
.- Exploring the benefits of iterative retrieval-augmented generation for risk mitiga tion in LLM response.
.- TrustAI: Designing and Implementing a Trustworthy and User-Centered AI Plat form.
.- Collaborative Trustworthy Foundation Model Framework: An Environmental  Sustainability Use-Case to Detect Contamination Objects in Organic Waste  Streams.
.- Optimisation of Industrial Production with AI Algorithms.
.- Efficient Federated Learning Integration into Existing MLOps Pipelines via Centralized Model Management.
.- Deep Photometric Stereo for Tool Wear Inspection.
.- Multi-Objective Reinforcement Learning for Energy-Efficient Industrial Control.
.- Deep learning-based defect detection in laser powder bed fusion.
.- Prediction of CNC Manufacturing Time Under Real-World Conditions Using  Graph Convolutional Networks.
.- A Vision-Guided Approach to Pick-and-Place Robotics: From Assembly Drawings to Industrial Assembly Automation.
.- Towards Real-time Tool Wear Detection on Edge Devices: A Lightweight Di mensionality Reduction Approach for Spindle Integrated Cutting Force Sensor 
Data.
.- Energy Optimized Piecewise Polynomial Approximation Utilizing Modern Ma chine Learning Optimizers.

Zusammenfassung

This volume constitutes the refereed proceedings of the 7th International Workshop on AI System Engineering: Math, Modelling and Software, AISys 2025 and the First International Workshop on Optimisation of Industrial Production with AI Algorithms, AI4IP, co-located with the 36th International Conference on Database and Expert Systems Applications, DEXA 2025, which took place in Bangkok, Thailand, during August 25-27, 2025.
The 11 full papers were thoroughly reviewed and selected from a total of 23 submissions. They are organized in topical sections as follows: AI System Engineering: Math, Modelling and Software; and Optimization of Industrial Production with AI Algorithms.

Produktdetails

Mitarbeit Lukas Fischer (Herausgeber), Ulrich Göhner (Herausgeber), Sebnem Gül-Ficici (Herausgeber), Sebnem Gül-Ficici et al (Herausgeber), Sebnem Gül-Ficicir (Herausgeber), Sebnem Gül-Ficicir et al (Herausgeber), Dirk Jacob (Herausgeber), Ismail Khalil (Herausgeber), Gabriele Kotsis (Herausgeber), A Min Tjoa (Herausgeber), A Min Tjoa (Herausgeber), A. Min Tjoa (Herausgeber)
Verlag Springer, Berlin
 
Originaltitel Database and Expert Systems Applications - DEXA 2024 Workshops
Sprache Englisch
Produktform Taschenbuch
Erschienen 10.09.2025
 
EAN 9783032020024
ISBN 978-3-0-3202002-4
Seiten 116
Abmessung 155 mm x 7 mm x 235 mm
Gewicht 207 g
Illustration X, 116 p. 46 illus., 39 illus. in color.
Serie Communications in Computer and Information Science
Themen Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik

Software, Künstliche Intelligenz, Computerhardware, Algorithmen und Datenstrukturen, Software Engineering, Data Mining, Artificial Intelligence, Informationstheorie, Wissensbasierte Systeme, Expertensysteme, Database Management, Modelling, Data Structures and Information Theory, Data Mining and Knowledge Discovery, Computer Engineering and Networks, AI Algorithms, Optimisation Large Data, Implementasion, AI System Engineering: Math

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