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[null,"1.","Record Nr.",null,"UNINA9911047670603321"]
[null,null,"Autore",null,"Fischer Lukas"]
[null,null,"Titolo",null,"Database and Expert Systems Applications - DEXA 2025 Workshops : AISys and AI4IP, Bangkok, Thailand, August 25–27, 2025, Proceedings / / edited by Lukas Fischer, Ulrich Göhner, Sebnem Gül-Ficici, Dirk Jacob, Gabriele Kotsis, A Min Tjoa, Ismail Khalil"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026"]
[null,null,"ISBN",null,"3-032-02003-4"]
[null,null,"Edizione",null,"[1st ed. 2026.]"]
[null,null,"Descrizione fisica",null,"1 online resource (175 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 2615"]
[null,null,"Disciplina",null,"005.74"]
[null,null,"Soggetti",null,"Database management"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Data structures (Computer science)"]
[{"$nulls":4},"Information theory"]
[{"$nulls":4},"Software engineering"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Database Management"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Data Structures and Information Theory"]
[{"$nulls":4},"Software Engineering"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Engineering and Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- AI System Engineering: Math, Modelling and Software.  -- Exploring the benefits of iterative retrieval-augmented generation for risk mitiga tion in LLM response.  -- TrustAI: Designing and Implementing a Trustworthy and User-Centered AI Plat form.  -- Collaborative Trustworthy Foundation Model Framework: An Environmental Sustainability Use-Case to Detect Contamination Objects in Organic Waste Streams.  -- Optimisation of Industrial Production with AI Algorithms.  -- Efficient Federated Learning Integration into Existing MLOps Pipelines via Centralized Model Management.  -- Deep "]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","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."]