| Deep learning models for wireless signal classification with distributed low-cost spectrum sensors S Rajendran, W Meert, D Giustiniano, V Lenders, S Pollin IEEE Transactions on Cognitive Communications and Networking 4 (3), 433-445, 2018 | 111 | 2018 |
| Electrosense: Open and big spectrum data S Rajendran, R Calvo-Palomino, M Fuchs, B Van den Bergh, H Cordobés, ... IEEE Communications Magazine 56 (1), 210-217, 2017 | 36 | 2017 |
| Key technologies and system trade-offs for detection and localization of amateur drones MM Azari, H Sallouha, A Chiumento, S Rajendran, E Vinogradov, S Pollin IEEE Communications Magazine 56 (1), 51-57, 2018 | 35 | 2018 |
| SAIFE: Unsupervised wireless spectrum anomaly detection with interpretable features S Rajendran, W Meert, V Lenders, S Pollin 2018 IEEE International Symposium on Dynamic Spectrum Access Networks …, 2018 | 13 | 2018 |
| IEEE 5G spectrum sharing challenge: A practical evaluation of learning and feedback S Rajendran, B Van den Bergh, T Vermeulen, S Pollin IEEE Communications Magazine 54 (11), 210-216, 2016 | 11 | 2016 |
| DySPAN spectrum challenge: situational awareness and opportunistic spectrum access benchmarked F Wunsch, F Paisana, S Rajendran, A Selim, P Alvarez, S Müller, ... IEEE Transactions on Cognitive Communications and Networking 3 (3), 550-562, 2017 | 8 | 2017 |
| Saving energy in WSNs for acoustic surveillance applications while maintaining QoS B Thoen, G Ottoy, F Rosas, S Lauwereins, S Rajendran, L De Strycker, ... 2017 IEEE Sensors Applications Symposium (SAS), 1-6, 2017 | 7 | 2017 |
| Electrosense: Crowdsourcing spectrum monitoring B Van den Bergh, D Giustiniano, H Cordobés, M Fuchs, ... 2017 IEEE International Symposium on Dynamic Spectrum Access Networks …, 2017 | 5 | 2017 |
| Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features S Rajendran, W Meert, V Lenders, S Pollin IEEE Transactions on Cognitive Communications and Networking 5 (3), 637-647, 2019 | 3 | 2019 |
| Electrosense+: Empowering People to Decode the Radio Spectrum R Calvo-Palomino, H Cordobés, M Engel, M Fuchs, P Jain, M Liechti, ... arXiv preprint arXiv:1811.12265, 2018 | 2 | 2018 |
| Crowdsourced wireless spectrum anomaly detection S Rajendran, V Lenders, W Meert, S Pollin IEEE Transactions on Cognitive Communications and Networking, 2019 | 1 | 2019 |
| Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs H Sallouha, A Chiumento, S Rajendran, S Pollin IEEE Internet of Things Journal 6 (6), 9375-9385, 2019 | 1 | 2019 |
| Large-scale Wireless Spectrum Monitoring: Challenges and Solutions based on Machine Learning S Rajendran, S Pollin Spectrum Sharing: The Next Frontier in Wireless Networks, 2020 | | 2020 |
| Automatic Modulation Classification Using Parallel Fusion of Convolutional Neural Networks E Perenda, S Rajendran, S Pollin IEEE WIRELESS COMMUNICATIONS, 2019 | | 2019 |
| Deep Learning Solutions for Large Scale Wireless Spectrum Monitoring S Rajendran KU Leuven, 2019 | | 2019 |
| A multi-layered energy consumption model for smart wireless acoustic sensor networks G Dekkers, F Rosas, S Lauwereins, S Rajendran, S Pollin, B Vanrumste, ... arXiv preprint arXiv:1812.06672, 2018 | | 2018 |
| Electrosense-spectrum sensing with increased frequency range F Minucci, B Van den Bergh, S Rajendran, D Giustiniano, ... | | 2018 |
| Using Cheap RTL-SDRs for Measuring Electrosmog B Reynders, R Iyare, S Rajendran, V Volskiy, GAE Vandenbosch, S Pollin 2018 IEEE Symposium on Communications and Vehicular Technology (SCVT)(SCVT'18), 2018 | | 2018 |
| Key Technologies and System Trade-Offs for Detection and Localization of Amateur Drones M Mahdi Azari, H Sallouha, A Chiumento, S Rajendran, E Vinogradov, ... arXiv preprint arXiv:1710.08478, 2017 | | 2017 |
| Adaptive Channel Selection and Sensing based on Reinforcement Learning S Rajendran, S Pollin WIC/IEEE SP Symposium on Information Theory and Signal Processing, Date …, 2015 | | 2015 |
sofie pollinAssociate Professor Electrical Engineering, KU LeuvenVerified email at esat.kuleuven.be
