| Automatic pigment identification from hyperspectral data B Grabowski, W Masarczyk, P Głomb, A Mendys Journal of Cultural Heritage 31, 1-12, 2018 | 124 | 2018 |
| Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach M Romaszewski, P Głomb, M Cholewa ISPRS Journal of Photogrammetry and Remote Sensing 121, 60-76, 2016 | 68 | 2016 |
| Detection of interest points on 3D data: Extending the harris operator P Głomb Computer Recognition Systems 3, 103-111, 2009 | 51 | 2009 |
| Application of hyperspectral imaging and machine learning methods for the detection of gunshot residue patterns P Głomb, M Romaszewski, M Cholewa, K Domino Forensic science international 290, 227-237, 2018 | 49 | 2018 |
| Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks K Książek, M Romaszewski, P Głomb, B Grabowski, M Cholewa Sensors 20 (22), 6666, 2020 | 42 | 2020 |
| A dataset for evaluating blood detection in hyperspectral images M Romaszewski, P Głomb, A Sochan, M Cholewa Forensic Science International 320, 110701, 2021 | 37 | 2021 |
| Estimation of the number of states for gesture recognition with Hidden Markov Models based on the number of critical points in time sequence M Cholewa, P Głomb Pattern Recognition Letters 34 (5), 574-579, 2013 | 32 | 2013 |
| Choosing and modeling the hand gesture database for a natural user interface P Głomb, M Romaszewski, S Opozda, A Sochan Gesture and Sign Language in Human-Computer Interaction and Embodied …, 2012 | 27 | 2012 |
| Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling W Masarczyk, P Głomb, B Grabowski, M Ostaszewski Remote Sensing 12 (16), 2653, 2020 | 26 | 2020 |
| Quantum hidden Markov models based on transition operation matrices M Cholewa, P Gawron, P Głomb, D Kurzyk Quantum Information Processing 16 (4), 101, 2017 | 25 | 2017 |
| A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification M Cholewa, P Głomb, M Romaszewski IEEE Geoscience and Remote Sensing Letters 16 (3), 467-471, 2019 | 12 | 2019 |
| Unsupervised parameter selection for gesture recognition with vector quantization and hidden markov models P Głomb, M Romaszewski, A Sochan, S Opozda IFIP Conference on Human-Computer Interaction, 170-177, 2011 | 12 | 2011 |
| Detection of emergent leaks using machine learning approaches P Głomb, M Cholewa, W Koral, A Madej, M Romaszewski Water Supply 23 (6), 2370-2386, 2023 | 10 | 2023 |
| Classification and Self-Supervised Regression of Arrhythmic ECG Signals Using Convolutional Neural Networks B Grabowski, P Głomb, W Masarczyk, P Pławiak, Ö Yıldırım, UR Acharya, ... arXiv preprint arXiv:2210.14253, 2022 | 9 | 2022 |
| Anomaly detection in hyperspectral remote sensing images P Głomb, M Romaszewski Hyperspectral Remote Sensing, 45-66, 2020 | 8 | 2020 |
| Eigengestures for natural human computer interface P Gawron, P Głomb, JA Miszczak, Z Puchała Man-Machine Interactions 2, 49-56, 2011 | 8 | 2011 |
| Energy-Aware Algorithm for Assignment of Relays in LP WAN K Grochla, A Strzoda, R Marjasz, P Głomb, K Książek, Z Łaskarzewski ACM Transactions on Sensor Networks 18 (4), 1-23, 2022 | 7 | 2022 |
| 3d mesh approximation using vector quantization M Romaszewski, P Głomb Computer Recognition Systems 3, 71-78, 2009 | 7 | 2009 |
| Hyper-Spectral Image Classification Using Adiabatic Quantum Computation B Gardas, P Głomb, P Sadowski, Z Puchała, K Jałowiecki, Ł Pawela, ... IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | 6 | 2023 |
| Natural human gestures classification using multisensor data M Cholewa, P Głomb 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 499-503, 2015 | 6 | 2015 |
Michał CholewaInstitute of Theoretical and Applied InformaticsVerified email at iitis.pl
