Data analytics for industrial process improvement a vision paper S Thalmann, J Mangler, T Schreck, C Huemer, M Streit, F Pauker, ... 2018 IEEE 20th Conference on Business Informatics (CBI) 2, 92-96, 2018 | 27 | 2018 |
State-of-the-art explainability methods with focus on visual analytics showcased by glioma classification M Gashi, M Vuković, N Jekic, S Thalmann, A Holzinger, C Jean-Quartier, ... BioMedInformatics 2 (1), 139-158, 2022 | 24 | 2022 |
Cognitive decision support for industrial product life cycles: A position paper S Thalmann, HG Gursch, J Suschnigg, M Gashi, H Ennsbrunner, ... Proceedings of the 11 th International Conference on Advanced Cognitive …, 2019 | 17 | 2019 |
Dealing with missing usage data in defect prediction: A case study of a welding supplier M Gashi, P Ofner, H Ennsbrunner, S Thalmann Computers in industry 132, 103505, 2021 | 15 | 2021 |
Taking complexity into account: A structured literature review on multi-component systems in the context of predictive maintenance M Gashi, S Thalmann Information Systems: 16th European, Mediterranean, and Middle Eastern …, 2020 | 13 | 2020 |
MEDEP: Maintenance event detection for multivariate time series based on the PELT approach M Gashi, H Gursch, H Hinterbichler, S Pichler, S Lindstaedt, S Thalmann Sensors 22 (8), 2837, 2022 | 6 | 2022 |
Decision support for multi-component systems: visualizing interdependencies for predictive maintenance. M Gashi, B Mutlu, SN Lindstaedt, S Thalmann HICSS, 1-10, 2022 | 6 | 2022 |
Towards flexible and cognitive production—addressing the production challenges M Abdul Hadi, D Kraus, A Kajmakovic, J Suschnigg, O Guiza, M Gashi, ... Applied Sciences 12 (17), 8696, 2022 | 5 | 2022 |
Towards a task-based guidance in exploratory visual analytics B Mutlu, M Gashi, V Sabol 54th Annual Hawaii International Conference on System Sciences: HICSS 2021 …, 2021 | 5 | 2021 |
Interactive Visual Exploration of defect prediction in industrial setting through explainable models based on SHAP values M Gashi, B Mutlu, J Suschnigg, P Ofner, S Pichler, T Schreck IEEE VIS 2020, 2020 | 5 | 2020 |
Impact of interdependencies: Multi-component system perspective toward predictive maintenance based on machine learning and XAI M Gashi, B Mutlu, S Thalmann Applied Sciences 13 (5), 3088, 2023 | 2 | 2023 |
No Time to Crash: Visualizing Interdependencies for Optimal Maintenance Scheduling M Gashi, B Mutlu, S Lindstaedt, S Thalmann Proceedings of the Cognitive, 2022 | 2 | 2022 |
" Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier-DOI) S Thalmann, J Mangler, T Schreck, C Huemer, M Streit, F Pauker, ... | 2 | |
Accurate and Efficient Hybrid Indoor Localization using ML Methods M Gashi, L Botler, G Koutroulis, K Diwold 2022 21st ACM/IEEE International Conference on Information Processing in …, 2022 | 1 | 2022 |
Machine Learning-based Models for Phase-Difference-of-Arrival Measurements Using Ultra-Wideband Transceivers L Botler, M Gashi, K Diwold, K Römer 2022 21st ACM/IEEE International Conference on Information Processing in …, 2022 | 1 | 2022 |
Improving the Planning Quality in Practice with Artificial Intelligence L Czarnetzki, D Karnok, J Breitschopf, M Karner, M Gashi IMEKO, 2023 | | 2023 |
A paradox approach to detect internal defects of a production part MA Hadi, M Gashi, V Manjunath, S Trabesinger, J Schmid | | 2022 |
Data Analytics for Industrial Process Improvement A Vision Paper S Rinderle-Ma, J Mangler, S Thalmann, T Schreck, C Huemer, M Streit, ... | | 2018 |
Goal oriented Visual Recommendations via User Behavior Analysis M Gashi Institute of Interactive Systems and Data Science, 2018 | | 2018 |
2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)| 978-1-6654-9624-7/22/$31.00© 2022 IEEE| DOI: 10.1109/IPSN54338. 2022.00073 E Abel-Rahman, D Agrawal, A Alali, MI Ali, A Ashok, F Bambusi, Y Bartan, ... | | |