End-to-end learning from spectrum data: A deep learning approach for wireless signal identification in spectrum monitoring applications M Kulin, T Kazaz, I Moerman, E De Poorter IEEE access 6, 18484-18501, 2018 | 366 | 2018 |
A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer M Kulin, T Kazaz, E De Poorter, I Moerman Electronics 10 (3), 318, 2021 | 92 | 2021 |
Data-driven design of intelligent wireless networks: An overview and tutorial M Kulin, C Fortuna, E De Poorter, D Deschrijver, I Moerman Sensors 16 (6), 790, 2016 | 86 | 2016 |
Wireless technology recognition based on RSSI distribution at sub-Nyquist sampling rate for constrained devices W Liu, M Kulin, T Kazaz, A Shahid, I Moerman, E De Poorter Sensors 17 (9), 2081, 2017 | 43 | 2017 |
Hardware accelerated SDR platform for adaptive air interfaces T Kazaz, C Van Praet, M Kulin, P Willemen, I Moerman arXiv preprint arXiv:1705.00115, 2017 | 27 | 2017 |
SIP server security with TLS: Relative performance evaluation M Kulin, T Kazaz, S Mrdovic Telecommunications (BIHTEL), 2012 IX International Symposium on, 1-6, 2012 | 22 | 2012 |
Design and implementation of SDR based QPSK modulator on FPGA T Kazaz, M Kulin, M Hadzialic 2013 36th International Convention on Information and Communication …, 2013 | 21 | 2013 |
Poster: Towards a Cognitive MAC Layer: Predicting the MAC-level Performance in Dynamic WSN using Machine Learning. M Kulin, E De Poorter, T Kazaz, I Moerman EWSN, 214-215, 2017 | 12 | 2017 |
One approach to the development of custom SNMP agents and integration with management systems T Kazaz, M Kulin, E Kaljić, T Čaršimanović 2012 Proceedings of the 35th International Convention MIPRO, 557-561, 2012 | 6 | 2012 |
WiSCoP-Wireless Sensor Communication Prototyping Platform T Kazaz, X Jiao, M Kulin, I Moerman arXiv preprint arXiv:1612.02900, 2016 | 5 | 2016 |
Towards a cognitive MAC layer: Predicting the MAC-level performance in Dynamic WSN using Machine learning M Kulin, E De Poorter, T Kazaz, I Moerman arXiv preprint arXiv:1612.03932, 2016 | 4 | 2016 |
Poster: Towards a cognitive MAC layer: Predicting the MAC-level performance in Dynamic WSN using Machine learning M Kulin, E De Poorter, T Kazaz, I Moerman | 1 | |
A Survey on Machine Learning-Based Performance Improvement of Wireless Networks: PHY, MAC and Network Layer. Electronics 2021, 10, 318 M Kulin, T Kazaz, E De Poorter, I Moerman s Note: MDPI stays neu-tral with regard to jurisdictional clai-ms in …, 2021 | | 2021 |
Performance optimization of next-generation data-driven wireless networks: a machine learning approach M Kulin Ghent University, 2020 | | 2020 |
WiSHF L M Kulin, AZ TUB, MC TUB, P Gawłowicz | | |
Primjer izvedbe IMS za reprodukciju multimedijalnih sadržaja DDS Mrdović, M Kulin | | |