Buch, Englisch, 116 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 207 g
AISys and AI4IP, Bangkok, Thailand, August 25-27, 2025, Proceedings
Buch, Englisch, 116 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 207 g
Reihe: Communications in Computer and Information Science
ISBN: 978-3-032-02002-4
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Technische Informatik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
Weitere Infos & Material
.- 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.
