@inproceedings{AkmalAsifKovaletal.2025, author = {Akmal, Muhammad Uzair and Asif, Saara and Koval, Leonid and Mathias, Selvine George and Knollmeyer, Simon and Großmann, Daniel}, title = {Layered Data-Centric AI to Streamline Data Quality Practices for Enhanced Automation}, booktitle = {Artificial Intelligence: Methodology, Systems, and Applications: 19th International Conference, AIMSA 2024, Varna, Bulgaria, September 18-20, 2024, Proceedings}, editor = {Koprinkova-Hristova, Petia and Kasabov, Nikola}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-81542-3}, doi = {https://doi.org/10.1007/978-3-031-81542-3_11}, pages = {128 -- 142}, year = {2025}, language = {en} } @inproceedings{MathiasAsifAkmaletal.2025, author = {Mathias, Selvine George and Asif, Saara and Akmal, Muhammad Uzair and Knollmeyer, Simon and Koval, Leonid and Großmann, Daniel}, title = {Industrial Image Grouping Through Pre-Trained CNN Encoder-Based Feature Extraction and Sub-Clustering}, booktitle = {Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) - Volume 2}, editor = {Rocha, Ana Paula and Steels, Luc and van den Herik, Jaap}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-737-5}, doi = {https://doi.org/10.5220/0013189000003890}, pages = {496 -- 506}, year = {2025}, abstract = {A common challenge faced by many industries today is the classification of unlabeled image data from production processes into meaningful groups or patterns for better documentation and analysis. This paper presents a sequential approach for leveraging industrial image data to identify patterns in products or processes for plant floor operators. The dataset used is sourced from steel production, and the model architecture integrates feature reduction through convolutional neural networks (CNNs) like VGG, EfficientNet, and ResNet, followed by clustering algorithms to assign appropriate labels to the observed data. The model's selection criteria combine clustering metrics, including entropy minimization and silhouette score maximization. Once primary clusters are identified, sub-clustering is performed using near-labels, which are pre-assigned to images with initial distinctions. A novel metric, C-Score, is introduced to assess cluster convergence and grouping accuracy. Experimental re sults demonstrate that this method can address challenges in detecting variations across images, improving pattern recognition and classification.}, language = {en} } @inproceedings{KovalAkmalAsifetal.2025, author = {Koval, Leonid and Akmal, Muhammad Uzair and Asif, Saara and Mathias, Selvine George and Knollmeyer, Simon and Großmann, Daniel}, title = {Optimizing AI-Driven Production in Industry 4.0: A Morphological Box and Taxonomy Approach}, booktitle = {2025 International Conference on Computer Technology Applications (ICCTA)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-1265-1}, doi = {https://doi.org/10.1109/ICCTA65425.2025.11166106}, pages = {272 -- 278}, year = {2025}, language = {en} } @inproceedings{MathiasAkmalAsifetal.2025, author = {Mathias, Selvine George and Akmal, Muhammad Uzair and Asif, Saara and Knollmeyer, Simon and Koval, Leonid and Grossmann, Daniel}, title = {Handling Anonymized Non-numerical Features in Data Using Transformations for Regression Models}, booktitle = {Artificial Intelligence Applications and Innovations: 21st IFIP WG 12.5 International Conference, AIAI 2025, Limassol, Cyprus, June 26-29, 2025, Proceedings, Part III}, editor = {Maglogiannis, Ilias and Iliadis, Lazaros and Andreou, Andreas and Papaleonidas, Antonios}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-96231-8}, doi = {https://doi.org/10.1007/978-3-031-96231-8_8}, pages = {99 -- 111}, year = {2025}, language = {en} } @inproceedings{AkmalMathiasAsifetal.2025, author = {Akmal, Muhammad Uzair and Mathias, Selvine George and Asif, Saara and Koval, Leonid and Knollmeyer, Simon and Großmann, Daniel}, title = {Humanizing AI: A Human-Centered Architecture to Developing Trustworthy Intelligent Systems}, booktitle = {CS \& IT Conference Proceedings}, publisher = {AIRCC}, address = {[s. l.]}, isbn = {978-1-923107-57-1}, url = {https://www.csitcp.com/abstract/15/158csit03}, pages = {27 -- 44}, year = {2025}, language = {en} }