Michal Cholewa
Orcid: 0000-0001-6549-1590
According to our database1,
Michal Cholewa
authored at least 21 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
'Just One More Sensor is Enough' - Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors.
CoRR, 2024
Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models.
CoRR, 2024
2023
Continual learning of a time series model using a mixture of HMMs with application to the IoT fuel sensor verification.
Proceedings of the 18th Conference on Computer Science and Intelligence Systems, 2023
2022
Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation.
Proceedings of the Image Analysis and Processing - ICIAP 2022, 2022
2021
2020
Sensors, 2020
2019
A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification.
IEEE Geosci. Remote. Sens. Lett., 2019
2018
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images.
CoRR, 2018
Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data.
Proceedings of the Computer and Information Sciences - 32nd International Symposium, 2018
2017
Quantum Inf. Process., 2017
2016
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), 2016
Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods, 2016
2015
Proceedings of the Artificial Intelligence and Soft Computing, 2015
Relation of Average Error in Prolate Spheroidal Wave Functions Algorithm for Bandlimited Functions Approximation to Radius of Information.
Proceedings of the Artificial Intelligence and Soft Computing, 2015
Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition, 2015
2014
Proceedings of the Artificial Intelligence and Soft Computing, 2014
2013
Estimation of the number of states for gesture recognition with Hidden Markov Models based on the number of critical points in time sequence.
Pattern Recognit. Lett., 2013
2011
Proceedings of the Computer Recognition Systems 4, 2011
Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data
CoRR, 2011