| Unsupervised Anomaly Based Botnet Detection in IoT Networks S Nõmm, H Bahşi 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 127 | 2018 |
| MedBIoT: Generation of an IoT Botnet Dataset in a Medium-sized IoT Network. A Guerra-Manzanares, J Medina-Galindo, H Bahsi, S Nõmm ICISSP, 207-218, 2020 | 119 | 2020 |
| Dimensionality Reduction for Machine Learning Based IoT Botnet Detection H Bahşi, S Nõmm, FB La Torre 2018 15th International Conference on Control, Automation, Robotics and …, 2018 | 119 | 2018 |
| KronoDroid: Time-based hybrid-featured dataset for effective android malware detection and characterization A Guerra-Manzanares, H Bahsi, S Nõmm Computers & Security 110, 102399, 2021 | 77 | 2021 |
| Hybrid feature selection models for machine learning based botnet detection in IoT networks A Guerra-Manzanares, H Bahsi, S Nõmm 2019 International Conference on Cyberworlds (CW), 324-327, 2019 | 58 | 2019 |
| On realizability of neural networks-based input–output models in the classical state-space form Ü Kotta, FN Chowdhury, S Nõmm Automatica 42 (7), 1211-1216, 2006 | 56 | 2006 |
| Neural networks based ANARX structure for identification and model based control E Petlenkov, S Nomm, U Kotta 2006 9th International Conference on Control, Automation, Robotics and …, 2006 | 39 | 2006 |
| On a new type of neural-network-based input-output model: the ANARMA structure Ü Kotta, S Nõmm, FN Chowdhury IFAC Proceedings Volumes 34 (6), 1535-1538, 2001 | 34 | 2001 |
| In-Depth Feature Selection for the Statistical Machine Learning-Based Botnet Detection in IoT Networks R Kalakoti, S Nõmm, H Bahsi IEEE Access 10, 94518 - 94535, 2022 | 32 | 2022 |
| Linear input-output equivalence and row reducedness of discrete-time nonlinear systems Ü Kotta, Z Bartosiewicz, S Nomm, E Pawluszewicz IEEE Transactions on Automatic Control 56 (6), 1421-1426, 2011 | 30 | 2011 |
| Detailed Analysis of the Luria's Alternating SeriesTests for Parkinson's Disease Diagnostics S Nõmm, K Bardõš, A Toomela, K Medijainen, P Taba 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 29 | 2018 |
| Tremor-related feature engineering for machine learning based Parkinson’s disease diagnostics E Valla, S Nõmm, K Medijainen, P Taba, A Toomela Biomedical Signal Processing and Control 75 (103551), 2022 | 28 | 2022 |
| Monitoring of the human motor functions rehabilitation by neural networks based system with kinect sensor S Nomm, K Buhhalko IFAC Proceedings Volumes 46 (15), 249-253, 2013 | 27 | 2013 |
| Classical state space realizability of input-output bilinear models Ü Kotta, S Nomm, ASI Zinober International Journal of Control 76 (12), 1224-1232, 2003 | 27 | 2003 |
| Quantitative analysis in the digital Luria's alternating series tests S Nomm, A Toomela, J Kozhenkina, T Toomsoo Control, Automation, Robotics and Vision (ICARCV), 2016 14th International …, 2016 | 26 | 2016 |
| An alternative approach to measure quantity and smoothness of the human limb motions. S Nõmm, A Toomela Estonian Journal of Engineering 19 (4), 2013 | 25 | 2013 |
| On realizability of neural networks-based input-output models FN Chowdhury, U Kotta, S Nõmm Proc. of the 3rd Int. Conf. on Differential Equations and Applications, St …, 2000 | 23 | 2000 |
| Nn-based anarx model of the surgeon's hand for the motion recognition 貞弘晃宜， 宮脇富士夫 Proceedings of the 4th COE Workshop on Human Adaptive Mechatronics (HAM), 19-24, 2007 | 20 | 2007 |
| Towards the Integration of a Post-Hoc Interpretation Step into the Machine Learning Workflow for IoT Botnet Detection A Guerra-Manzanares, S Nõmm, H Bahsi 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 19 | 2019 |
| Recognition of the surgeon's motions during endoscopic operation by statistics based algorithm and neural networks based ANARX models S Nomm, E Petlenkov, J Vain, J Belikov, F Miyawaki, K Yoshimitsu IFAC Proceedings Volumes 41 (2), 14773-14778, 2008 | 19 | 2008 |
