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2020 – today
- 2024
[j17]Ondrej Budik, Milan Novak, Florian Sobieczky, Ivo Bukovsky:
AISLEX: Approximate individual sample learning entropy with JAX. SoftwareX 28: 101915 (2024)- [c30]Pratik Goswami, Rudolf Vohnout, Amrit Mukherjee, Ivo Bukovsky:
Intelligent and Energy-Efficient Approach for Detecting Patient Locations. ICCE 2024: 1-6 - 2023
- [j16]Rudolf Vohnout
, Ivo Bukovsky, Shuo-Yan Chou, Jakub Geyer, Ondrej Budik, Rohit Sharma, Milos Prokýsek, Tomás Horváth, Annemie Wyckmans:
Living Lab Long-Term Sustainability in Hybrid Access Positive Energy Districts - A Prosumager Smart Fog Computing Perspective. IEEE Internet Things J. 10(21): 18898-18908 (2023) - [j15]Ivo Bukovsky, Gejza Dohnal, Peter Mark Benes, Kei Ichiji, Noriyasu Homma:
Letter on Convergence of In-Parameter-Linear Nonlinear Neural Architectures With Gradient Learnings. IEEE Trans. Neural Networks Learn. Syst. 34(8): 5189-5192 (2023) - [j14]Ivo Bukovsky, Gejza Dohnal, Noriyasu Homma:
Comments on "Convergence Analysis of Adaptive Exponential Functional Link Network". IEEE Trans. Neural Networks Learn. Syst. 34(9): 6677-6678 (2023) - [c29]Zhang Zhang, Xiaoyong Zhang, Kei Ichiji, Ivo Bukovsky, Shuo-Yan Chou, Noriyasu Homma:
How Different Data Sources Impact Deep Learning Performance in COVID-19 Diagnosis using Chest X-ray Images. IIAI-AAI 2023: 508-513 - 2022
- [j13]Maqbool Khan, Arshad Ahmad, Florian Sobieczky, Mario Pichler, Bernhard Alois Moser, Ivo Bukovsky:
A Systematic Mapping Study of Predictive Maintenance in SMEs. IEEE Access 10: 88738-88749 (2022) - [c28]Ivo Bukovsky, Ondrej Budik:
Learning Entropy: On Shannon vs. Machine-Learning-Based Information in Time Series. DEXA Workshops 2022: 402-415 - 2021
- [j12]Matous Cejnek, Oldrich Vysata, Martin Valis, Ivo Bukovsky:
Novelty detection-based approach for Alzheimer's disease and mild cognitive impairment diagnosis from EEG. Medical Biol. Eng. Comput. 59(11): 2287-2296 (2021) - [j11]Ivo Bukovsky:
Deterministic behavior of temperature field in turboprop engine via shallow neural networks. Neural Comput. Appl. 33(19): 13145-13161 (2021) - [i3]Ivo Bukovsky, Gejza Dohnal, Peter Mark Benes, Kei Ichiji, Noriyasu Homma:
A Letter on Convergence of In-Parameter-Linear Nonlinear Neural Architectures with Gradient Learnings. CoRR abs/2111.12877 (2021) - 2020
- [c27]Noriyasu Homma, Kyohei Noro, Xiaoyong Zhang, Yutaro Kon, Kei Ichiji, Ivo Bukovsky, Akiko Sato, Naoko Mori:
Human ability enhancement for reading mammographic masses by a deep learning technique. BIBM 2020: 2962-2964 - [c26]Noriyasu Homma, Xiaoyong Zhang, Amber Qureshi, Takuya Konno, Yusuke Kawasumi, Akihito Usui, Masato Funayama, Ivo Bukovsky, Kei Ichiji, Norihiro Sugita, Makoto Yoshizawa:
A Deep Learning Aided Drowning Diagnosis for Forensic Investigations using Post-Mortem Lung CT Images. EMBC 2020: 1262-1265
2010 – 2019
- 2019
- [j10]Ivo Bukovsky, Witold Kinsner, Noriyasu Homma:
Learning Entropy as a Learning-Based Information Concept. Entropy 21(2): 166 (2019) - 2018
- [j9]Matous Cejnek, Ivo Bukovsky:
Concept drift robust adaptive novelty detection for data streams. Neurocomputing 309: 46-53 (2018) - [c25]Peter Benes, Ivo Bukovsky:
An Input to State Stability Approach for Evaluation of Nonlinear Control Loops with Linear Plant Model. CSOC (3) 2018: 144-154 - 2017
- [j8]Ivo Bukovsky, Noriyasu Homma:
An Approach to Stable Gradient-Descent Adaptation of Higher Order Neural Units. IEEE Trans. Neural Networks Learn. Syst. 28(9): 2022-2034 (2017) - [c24]Matous Cejnek, Ivo Bukovsky:
Influence of type and level of noise on the performance of an adaptive novelty detector. IEEE ICCI*CC 2017: 373-377 - [c23]Ivo Bukovsky, Jan Vorácek, Kei Ichiji, Noriyasu Homma:
Higher Order Neural Units for Efficient Adaptive Control of Weakly Nonlinear Systems. IJCCI 2017: 149-157 - [c22]Peter Mark Benes, Ivo Bukovsky, Martin Vesely, Jan Vorácek, Kei Ichiji, Noriyasu Homma:
Framework for Discrete-Time Model Reference Adaptive Control of Weakly Nonlinear Systems with HONUs. IJCCI (Selected Papers) 2017: 239-262 - 2016
- [c21]Peter Benes, Ivo Bukovsky:
On the Intrinsic Relation of Linear Dynamical Systems and Higher Order Neural Units. CSOC (3) 2016: 235-246 - [c20]Josef Bostik, Martin Klimt, Matej Mojzes, Jaromír Kukal, Ivo Bukovsky, Matous Cejnek:
V-shaped neurons in hidden layer of ANN universal approximator without flat domains. IJCNN 2016: 419-425 - [c19]Matous Cejnek, Ivo Bukovsky:
Online data centering modifications for adaptive filtering with NLMS algorithm. IJCNN 2016: 1767-1771 - [c18]Ivo Bukovsky, Matous Cejnek, Jan Vrba, Noriyasu Homma:
Study of Learning Entropy for onset detection of epileptic seizures in EEG time series. IJCNN 2016: 3302-3305 - [c17]Matej Mojzes, Martin Klimt, Jaromír Kukal, Ivo Bukovsky, Jan Vrba, Jan Pitel:
Feature selection via competitive levy flights. IJCNN 2016: 3731-3736 - [c16]Ivo Bukovsky, Peter Benes, Martin Vesely, Jan Pitel, Madan M. Gupta:
Model reference multiple-degree-of-freedom adaptive control with HONUs. IJCNN 2016: 4895-4900 - [i2]Ivo Bukovsky, Noriyasu Homma:
An Approach to Stable Gradient Descent Adaptation of Higher-Order Neural Units. CoRR abs/1606.07149 (2016) - 2015
- [c15]Ivo Bukovsky, Cyril Oswald:
Case Study of Learning Entropy for Adaptive Novelty Detection in Solid-Fuel Combustion Control. CSOC (2) 2015: 247-257 - [c14]Ivo Bukovsky, Peter Benes, Matous Slama:
Laboratory Systems Control with Adaptively Tuned Higher Order Neural Units. CSOC (2) 2015: 275-284 - [c13]Matous Cejnek, Ivo Bukovsky, Noriyasu Homma, Ondrej Liska:
Adaptive polynomial filters with individual learning rates for computationally efficient lung tumor motion prediction. IWCIM 2015: 1-5 - [c12]Matous Cejnek, Ivo Bukovsky, Oldrich Vysata:
Adaptive classification of EEG for dementia diagnosis. IWCIM 2015: 1-5 - [c11]Xiaoyong Zhang, Noriyasu Homma, Kei Ichiji, Makoto Abe, Norihiro Sugita, Ivo Bukovsky, Yoshihiro Takai, Makoto Yoshizawa:
Tumor motion tracking using kV/MV X-ray fluoroscopy for adaptive radiation therapy. IWCIM 2015: 1-4 - 2014
- [c10]Peter Benes, Ivo Bukovsky:
Neural network approach to hoist deceleration control. IJCNN 2014: 1864-1869 - [c9]Peter Michal, Jan Pitel, Alena Vagaská, Ivo Bukovsky:
Application of neural networks to evaluate experimental data of galvanic zincing. IJCNN 2014: 2997-3001 - [c8]Ivo Bukovsky, Noriyasu Homma, Matous Cejnek, Kei Ichiji:
Study of Learning Entropy for Novelty Detection in lung tumor motion prediction for target tracking radiation therapy. IJCNN 2014: 3124-3129 - [i1]Peter Mark Benes, Ivo Bukovsky, Matous Cejnek, Jan Kalivoda:
Neural Network Approach to Railway Stand Lateral Skew Control. CoRR abs/1402.7136 (2014) - 2013
- [j7]Ivo Bukovsky:
Learning Entropy: Multiscale Measure for Incremental Learning. Entropy 15(10): 4159-4187 (2013) - 2012
- [j6]Madan M. Gupta, Ivo Bukovsky, Noriyasu Homma, Zeng-Guang Hou, Ashu M. G. Solo:
Cognitive and Neural Aspects in Robotics with Applications 2011. J. Robotics 2012: 132360:1-132360:2 (2012) - 2011
- [j5]Ricardo Rodríguez Jorge, Ivo Bukovsky, Noriyasu Homma:
Potentials of Quadratic Neural Unit for Applications. Int. J. Softw. Sci. Comput. Intell. 3(3): 1-12 (2011) - [j4]Marco Baglietto, Lubica Benusková, Ivo Bukovsky, Tianping Chen, Tom Heskes, Kazushi Ikeda, Fakhri Karray, Rhee Man Kil, Robert Legenstein, Jinhu Lu, Yunqian Ma, Malik Magdon-Ismail, Michael G. Paulin, Robi Polikar, Danil V. Prokhorov, Marco A. Wiering, Vicente Zarzoso:
Editorial: One Year as EiC, and Editorial-Board Changes at TNN. IEEE Trans. Neural Networks 22(1): 1-7 (2011) - [c7]Kei Ichiji, Noriyasu Homma, Ivo Bukovsky, Makoto Yoshizawa:
Intelligent sensing of biomedical signals - Lung tumor motion prediction for accurate radiotherapy. CompSens 2011: 35-41 - [c6]Ivo Bukovsky, Witold Kinsner, Vladimir Maly, Karel Krehlik:
Multiscale Analysis of False Neighbors for state space reconstruction of complicated systems. CompSens 2011: 65-72 - 2010
- [j3]Madan M. Gupta, Noriyasu Homma, Zeng-Guang Hou, Ivo Bukovsky:
Cognitive and Neural Aspects in Robotics with Applications. J. Robotics 2010: 623140:1-623140:2 (2010) - [j2]Noriyasu Homma, Shinpei Kato, Takakuni Goto, Ivo Bukovsky, Ryuta Kawashima, Makoto Yoshizawa:
How Can Brain Learn to Control a Nonholonomic System? J. Robotics 2010: 919306:1-919306:7 (2010) - [c5]Ivo Bukovsky, Noriyasu Homma, L. Smetana, Ricardo Rodríguez Jorge, M. Mironovova, S. Vrana:
Quadratic neural unit is a good compromise between linear models and neural networks for industrial applications. IEEE ICCI 2010: 556-560 - [c4]Ivo Bukovsky, Kei Ichiji, Noriyasu Homma, Makoto Yoshizawa, Ricardo Rodríguez Jorge:
Testing potentials of dynamic quadratic neural unit for prediction of lung motion during respiration for tracking radiation therapy. IJCNN 2010: 1-6 - [c3]Ivo Bukovsky, Martin Lepold, Jirí Bíla:
Quadratic neural unit and its network in validation of process data of steam turbine loop and energetic boiler. IJCNN 2010: 1-7
2000 – 2009
- 2008
- [j1]Ivo Bukovsky, Zeng-Guang Hou, Jirí Bíla, Madan M. Gupta:
Foundations of Nonconventional Neural Units and their Classification. Int. J. Cogn. Informatics Nat. Intell. 2(4): 29-43 (2008) - [c2]Ivo Bukovsky, Jirí Bíla:
Adaptive evaluation of complex time series using nonconventional neural units. IEEE ICCI 2008: 128-137 - 2007
- [c1]Ivo Bukovsky, Zeng-Guang Hou, Jirí Bíla, Madan M. Gupta:
Foundation of Notation and Classification of Nonconventional Static and Dynamic Neural Units. IEEE ICCI 2007: 401-407
Coauthor Index
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