dr hab. inż. Przemysław Głomb

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0000-0002-0215-4674

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profesor instytutu
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Publikacje
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2024

1. Kołodziej, K., M. Cholewa, P. Głomb, W. Koral, and M. Romaszewski, "Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials", arXiv preprint arXiv:2410.02772, 09/2024.
2. Cholewa, M., M. Romaszewski, P. Głomb, K. Kołodziej, M. Gorawski, J. Koral, W. Koral, A. Madej, and K. Musioł, "‘Just One More Sensor is Enough’ – Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors", IEEE Sensors Journal, 06/2024.
3. Romaszewski, M., P. Sekuła, P. Głomb, M. Cholewa, and K. Kołodziej, "Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models", arXiv preprint arXiv:2406.04926, 06/2024.
4. Książek, K., "Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data", Computers in Biology and Medicine, vol. 176, 05/2024.

2023

5. Książek, K., W. Masarczyk, P. Głomb, M. Romaszewski, I. Stokłosa, P. Ścisło, P. Dębski, R. Pudlo, K. Buza, P. Gorczyca, et al., "The analysis of heart rate variability and accelerometer mobility data in the assessment of symptom severity in psychotic disorder patients using a wearable Polar H10 sensor", medXriv, 08/2023.
6. Strzoda, A., K. Grochla, P. Głomb, and A. Madej, "Link failure prediction in LoRa networks", International Wireless Communications and Mobile Computing Conference, IWCMC, Marrakesh, Morocco, IEEE, 07/2023.
7. Głomb, P., M. Cholewa, W. Koral, A. Madej, and M. Romaszewski, "Detection of emergent leaks using machine learning approaches", Water Supply, vol. 23, issue 6, 05/2023.
8. Książek, K., W. Masarczyk, P. Głomb, M. Romaszewski, I. Stokłosa, P. Ścisło, P. Dębski, R. Pudlo, P. Gorczyca, and M. Piegza, HRV-ACC: a dataset with R-R intervals and accelerometer data for the diagnosis of psychotic disorders using a Polar H10 wearable sensor, 2023.
9. Ciemięga, A., K. Maresz, M. Romaszewski, P. Głomb, P. Krupska-Wolas, and K. Prusik, "Hyperspectral Imaging as a Facile and Non-Destructive Method for Size Analysis of Gold Nanoparticles Deposited on Porous Materials", Particle & Particle Systems Characterization, 2023.
10. Buza, K., K. Książek, W. Masarczyk, P. Głomb, P. Gorczyca, and M. Piegza, "A Simple and Effective Classifier for the Detection of Psychotic Disorders based on Heart Rate Variability Time Series", Information Technologies – Applications and Theory 2023, vol. 3498, Tatranské Matliare, Knižnicné a edicné centrum, Fakulta matematiky, fyziky a informatiky, Univerzita Komenského, Mlynská dolina, Bratislava, 09/2023.
11. Gardas, B., P. Głomb, P. Sadowski, Z. Puchała, K. Jałowiecki, Ł. Pawela, O. Faucoz, P-M. Brunet, P. Gawron, M. Van Waveren, et al., "Hyper-Spectral Image Classification Using Adiabatic Quantum Computation", IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023.
12. Głomb, P., M. Romaszewski, M. Cholewa, W. Koral, A. Madej, M. Skrabski, and K. Kołodziej, "Machine Learning for Water Leak Detection and Localization in the WaterPrime Project", Wojciechowski A.(Ed.), Lipiński P.(Ed.)., Progress in Polish Artificial Intelligence Research 4, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.: Wydawnictwo Politechniki Łódzkiej, 2023.
13. Głomb, P., M. Cholewa, P. Foszner, and J. Bularz, "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, FedCSIS 2023, Warsaw, Poland, September 17-20, 2023, 2023.

2022

14. Grabowski, B., P. Głomb, K. Książek, and K. Buza, " Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering", Asian Conference on Intelligent Information and Database Systems, vol. 1716, Ho Chi Minh City, Vietnam, Springer, 11/2022.
15. Grochla, K., A. Strzoda, R. Marjasz, P. Głomb, K. Książek, and Z. Łaskarzewski, "Energy-Aware Algorithm for Assignment of Relays in LPWAN", Transactions on Sensor Networks, vol. 18, issue 4, 11/2022.
16. Książek, K., P. Głomb, M. Romaszewski, M. Cholewa, B. Grabowski, and K. Buza, "Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation", 21st International Conference on Image Analysis and Processing, vol. 13231, Lecce, Italy, Springer, Cham, 05/2022.

2021

17. Romaszewski, M., P. Głomb, A. Sochan, and M. Cholewa, "A dataset for evaluating blood detection in hyperspectral images", Forensic Science International, vol. 320, 2021.

2020

18. Romaszewski, M., P. Głomb, A. Sochan, and M. Cholewa, A Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set], 2020.
19. Masarczyk, W., P. Głomb, B. Grabowski, and M. Ostaszewski, "Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling", Remote Sensing, vol. 12, issue 16, 2020.
20. Głomb, P., and M. Romaszewski, "Anomaly detection in hyperspectral remote sensing images", Hyperspectral Remote Sensing: Theory & Applications: Elsevier, 2020.
21. Książek, K., M. Romaszewski, P. Głomb, B. Grabowski, and M. Cholewa, "Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks", Sensors, vol. 20, issue Recent Advances in Multi- and Hyperspectral Image Analysis, 11/2020.

2019

22. Cholewa, M., P. Głomb, and M. Romaszewski, "A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification", IEEE Geoscience and Remote Sensing Letters, vol. 16, pp. 467-471, March, 2019.
23. Głomb, P., K. Domino, M. Romaszewski, and M. Cholewa, "Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images", PP-RAI'2019, Wrocław, Poland, Wroclaw University of Science and Technology, pp. p. 121, 2019.
24. Grabowski, B., P. Głomb, M. Romaszewski, and M. Ostaszewski, "Unsupervised deep learning approach to hyperspectral anomaly detection", PP-RAI'2019, Wrocław, Poland, Wroclaw University of Science and Technology, 2019.

2018

25. Romaszewski, M., P. Głomb, and M. Cholewa, "Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data", Computer and Information Sciences: Springer International Publishing, 2018.

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Historia zmian

Data aktualizacji: 10/06/2022 - 10:42; autor zmian: Łukasz Zimny (lzimny@iitis.pl)