| Fundamentals of higher order neural networks for modeling and simulation MM Gupta, I Bukovsky, N Homma, AMG Solo, ZG Hou Artificial Higher Order Neural Networks for Modeling and Simulation, 103-133, 2013 | 53 | 2013 |
| Concept drift robust adaptive novelty detection for data streams M Cejnek, I Bukovsky Neurocomputing 309, 46-53, 2018 | 40 | 2018 |
| A fast neural network approach to predict lung tumor motion during respiration for radiation therapy applications I Bukovsky, N Homma, K Ichiji, M Cejnek, M Slama, PM Benes, J Bila BioMed research international 2015 (1), 489679, 2015 | 40 | 2015 |
| Novelty detection-based approach for Alzheimer’s disease and mild cognitive impairment diagnosis from EEG M Cejnek, O Vysata, M Valis, I Bukovsky Medical & Biological Engineering & Computing 59, 2287-2296, 2021 | 37 | 2021 |
| Quadratic and cubic neural units for identification and fast state feedback control of unknown nonlinear dynamic systems I Bukovsky, S Redlapalli, MM Gupta Fourth International Symposium on Uncertainty Modeling and Analysis, 2003 …, 2003 | 37 | 2003 |
| Learning entropy: Multiscale measure for incremental learning I Bukovsky Entropy 15 (10), 4159-4187, 2013 | 33 | 2013 |
| An approach to stable gradient-descent adaptation of higher order neural units I Bukovsky, N Homma IEEE transactions on neural networks and learning systems 28 (9), 2022-2034, 2016 | 27 | 2016 |
| Quadratic neural unit is a good compromise between linear models and neural networks for industrial applications I Bukovsky, N Homma, L Smetana, R Rodriguez, M Mironovova, S Vrana 9th IEEE International Conference on Cognitive Informatics (ICCI'10), 556-560, 2010 | 27 | 2010 |
| A deep learning aided drowning diagnosis for forensic investigations using post-mortem lung CT images N Homma, X Zhang, A Qureshi, T Konno, Y Kawasumi, A Usui, ... 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 26 | 2020 |
| Qualitative modeling and monitoring of selected ecosystem functions J Bila, J Jura, J Pokorny, I Bukovsky Ecological modelling 222 (19), 3640-3650, 2011 | 25 | 2011 |
| Higher order neural networks: fundamental theory and applications MM Gupta, N Homma, ZG Hou, AMG Solo, I Bukovsky Artificial higher order neural networks for computer science and engineering …, 2010 | 23 | 2010 |
| Modeling of complex dynamic systems by nonconventional artificial neural architectures and adaptive approach to evaluation of chaotic time series I Bukovsky Unpublished doctoral dissertation, Faculty of Mechanical Engineering, Czech …, 2007 | 21 | 2007 |
| Learning entropy for novelty detection a cognitive approach for adaptive filters I Bukovsky, C Oswald, M Cejnek, PM Benes 2014 Sensor Signal Processing for Defence (SSPD), 1-5, 2014 | 18 | 2014 |
| Learning entropy as a learning-based information concept I Bukovsky, W Kinsner, N Homma Entropy 21 (2), 166, 2019 | 17 | 2019 |
| Multiscale analysis approach for novelty detection in adaptation plot I Bukovsky, W Kinsner, J Bila IET Digital Library, 2012 | 17 | 2012 |
| Potentials of quadratic neural unit for applications R Rodriguez, I Bukovsky, N Homma International Journal of Software Science and Computational Intelligence …, 2011 | 17 | 2011 |
| Foundation of notation and classification of nonconventional static and dynamic neural units I Bukovsky, ZG Hou, J Bila, MM Gupta 6th IEEE International Conference on Cognitive Informatics, 401-407, 2007 | 17 | 2007 |
| Quadratic neural unit and its network in validation of process data of steam turbine loop and energetic boiler I Bukovsky, M Lepold, J Bila The 2010 International joint conference on neural networks (IJCNN), 1-7, 2010 | 16 | 2010 |
| Foundations of nonconventional neural units and their classification I Bukovsky, ZG Hou, J Bila, MM Gupta International Journal of Cognitive Informatics and Natural Intelligence …, 2008 | 16 | 2008 |
| Testing potentials of dynamic quadratic neural unit for prediction of lung motion during respiration for tracking radiation therapy I Bukovsky, K Ichiji, N Homma, M Yoshizawa, R Rodriguez The 2010 International Joint Conference on Neural Networks (IJCNN), 1-6, 2010 | 15 | 2010 |
