Distributed spectrum sharing by reinforcement and game theory M Bublin, J Pan, I Kambourov, P Slanina 5th Karlsruhe workshop on software radio, Karlsruhe, Germany, 2008 | 17 | 2008 |
Event detection for distributed acoustic sensing: Combining knowledge-based, classical machine learning, and deep learning approaches M Bublin Sensors 21 (22), 7527, 2021 | 15 | 2021 |
A cost-function-based dynamic channel allocation and its limits M Bublin, M Konegger, P Slanina IEEE transactions on vehicular technology 56 (4), 2286-2295, 2007 | 13 | 2007 |
A deep learning approach for real time process monitoring and curling defect detection in Selective Laser Sintering by infrared thermography and convolutional neural networks V Klamert, M Schmid-Kietreiber, M Bublin Procedia CIRP 111, 317-320, 2022 | 10 | 2022 |
Interference avoidance concepts M Abaii, G Auer, F Bokhari, M Bublin, E Hardouin, O Hrdlicka, G Mange, ... Techical Report, IST-4–027756 WINNER II, D4. 7.2 v1. 0, 2007 | 10 | 2007 |
Inter-cell interference management by dynamic channel allocation, scheduling and smart antennas M Bublin, I Kambourov, P Slanina, D Bosanska, O Hlinka, O Hrdlicka, ... 2007 16th IST Mobile and Wireless Communications Summit, 1-5, 2007 | 7 | 2007 |
Machine learning for distributed acoustic sensors, classic versus image and deep neural networks approach M Bublin arXiv preprint arXiv:1904.11546, 2019 | 6 | 2019 |
Spectrum and Infrastructure Sharing in Wireless Mobile Networks: Advantages and Risks M Bublin, S Čaušević Promet-Traffic&Transportation 20 (4), 251-255, 2008 | 6 | 2008 |
Interference averaging concepts M Bublin, E Hardouin, O Hrdlicka, I Kambourov, R Legouable, M Olsson, ... Deliverable of the European Union project" Winner", IST-4-027756 WNNER II, 2007 | 5 | 2007 |
In Situ Analysis of Curling Defects in Powder Bed Fusion of Polyamide by Simultaneous Application of Laser Profilometry and Thermal Imaging V Klamert, L Schiefermair, M Bublin, A Otto Applied Sciences 13 (12), 7179, 2023 | 3 | 2023 |
Handwriting Evaluation Using Deep Learning with SensoGrip M Bublin, F Werner, A Kerschbaumer, G Korak, S Geyer, L Rettinger, ... Sensors 23 (11), 5215, 2023 | 2 | 2023 |
Automated dysgraphia detection by deep learning with SensoGrip M Bublin, F Werner, A Kerschbaumer, G Korak, S Geyer, L Rettinger, ... arXiv preprint arXiv:2210.07659, 2022 | 2 | 2022 |
Educating ai software engineers: Challenges and opportunities M Bublin, S Schefer-Wenzl, I Miladinović International Conference on Interactive Collaborative Learning, 241-251, 2021 | 2 | 2021 |
A cognitive pilot channel system design approach J Pan, P Slanina, T Renk, M Bublin, I Kambourov 5th Karlsruhe Workshop on Software Radios, 2008 | 2 | 2008 |
Comparison of interference based dynamic channel allocation algorithms in mobile networks M Bublin, G Ostermayer Proc. IEEE SoftCOM, 2003 | 2 | 2003 |
IST-4-027756 WINNER II D4. 7.2 v1. 0 interference avoidance concepts M Abaii, G Auer, F Bokhari, M Bublin, E Hardouin, O Hrdlicka, G Mange, ... Wireless World Initiative New Radio (WINNER), Tech. Rep, 0 | 2 | |
Real-Time Optical Detection of Artificial Coating Defects in PBF-LB/P Using a Low-Cost Camera Solution and Convolutional Neural Networks V Klamert, T Achsel, E Toker, M Bublin, A Otto Applied Sciences 13 (20), 11273, 2023 | | 2023 |
AI-POWERED EDUCATION: UNLEASHING THE POTENTIAL OF CHATGPT IN COMPUTER SCIENCE HIGHER EDUCATION S Schefer-Wenzl, I Miladinovic, M Bublin, L Freudenthaler, R Goldschmid, ... ICERI2023 Proceedings, 4886-4893, 2023 | | 2023 |
Robustheits-Index für die Objekterkennung am Beispiel eines People Movers W Schröter, DIA Gerstinger, M Bublin | | 2022 |
A Self-Adaptive, Utility-based Scheduling for Wireless Cellular Networks M Bublin, D Bosanska, O Hlinka, P Slanina 2007 16th IST Mobile and Wireless Communications Summit, 1-5, 2007 | | 2007 |