Przemysław Głomb, PhD

Email: 

Orcid ID: 

0000-0002-0215-4674

Position: 

Institute Professor
Research groups

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Publications
Biblio RSS

2019

26. 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.
27. 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.
28. 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

29. Grabowski, B., W. Masarczyk, P. Głomb, and A. Mendys, "Automatic pigment identification from hyperspectral data", Journal of Cultural Heritage, vol. 31, pp. 1 - 12, 2018.
30. 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.
31. Głomb, P., M. Romaszewski, M. Cholewa, and K. Domino, "Application of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns", Forensic Science International, vol. 290, 07/2018.

2017

32. Cholewa, M., P. Gawron, P. Głomb, and D. Kurzyk, "Quantum hidden Markov models based on transition operation matrices", Quantum Information Processing, vol. 16, pp. 101, 2017.

2016

33. Romaszewski, M., and P. Głomb, "Parameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences", Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2016.
34. Romaszewski, M., P. Głomb, and M. Cholewa, "Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 121, pp. 60 - 76, 2016.
35. Głomb, P., and M. Cholewa, "Performance of Interest Point Descriptors on Hyperspectral Images", Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, 2016.
36. Cholewa, M., and P. Głomb, "Two Stage SVM Classification for Hyperspectral Data", Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, 2016.

2015

37. Domino, K., P. Głomb, and Z. Łaskarzewski, "Classification of LPG clients using the Hurst exponent and the correlation coeficient", Theoretical and Applied Informatics, vol. 27, issue 1, pp. 13–24, 2015.
38. Głomb, P., and M. Cholewa, "Experimental Evaluation of Selected Approaches to Covariance Matrix Regularization", Artificial Intelligence and Soft Computing, vol. 9120: Springer International Publishing, pp. 391-401, 2015.

2014

39. Romaszewski, M., P. Głomb, and P. Gawron, "Natural hand gestures for human identification in a Human-Computer Interface", Image Processing Theory Tools and Applications (IPTA), 2014 4th International Conference on: IEEE, pp. 404–409, 10, 2014.
40. Głomb, P., and A. Sochan, "Surface Mixture Models for the Optimization of Object Boundary Representation", Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science 8467, pp. 703–714, 2014.

2013

41. Cholewa, M., P. Głomb, S. Opozda, M. Romaszewski, A. Sochan, M. Kosiedowski, E. Kuśmierek, A. Bęben, P. Krawiec, and A. Stroiński, "Aplikacje Sieci Świadomej Treści", Inżynieria Internetu przyszłości część 2: Oficyna Wydawnicza PW, 2013.

2012

42. Cholewa, M., and P. Głomb, "Estimation of the number of states for gesture recognition with Hidden Markov Models based on the number of critical points in time sequence", Pattern Recognition Letters, 2012.
43. Blachnik, M., and P. Głomb, "Do we need complex models for gestures? A comparison of data representation and preprocessing methods for hand gesture recognition", Artificial Intelligence and Soft Computing Lecture Notes in Computer Science 7267: Springer Berlin Heidelberg, pp. 477–485, 2012.
44. Głomb, P., M. Romaszewski, S. Opozda, and A. Sochan, "Choosing and Modeling the Hand Gesture Database for a Natural User Interface", Gesture and Sign Language in Human-Computer Interaction and Embodied Communication, Lecture Notes in Artificial Intelligence: Springer Berlin Heidelberg, 2012.
45. Kosiedowski, M., E. Kuśmierek, A. Stroiński, M. Cholewa, P. Głomb, S. Opozda, M. Romaszewski, A. Sochan, A. Bęben, and P. Krawiec, "Aplikacje sieci świadomej treści", Przegląd telekomunikacyjny, no. 8-9, pp. 1491–1502, 2012.

2011

46. Romaszewski, M., P. Gawron, and P. Głomb, Towards a natural gesture interface: LDA-based gesture separability, 2011.
47. Gawron, P., P. Głomb, J. Miszczak, and Z. Puchała, "Eigengestures for natural human computer interface", Man-Machine Interactions 2, Berlin / Heidelberg, Springer, pp. 49–56, 2011.
48. Głomb, P., M. Romaszewski, S. Opozda, and A. Sochan, "Choosing and modeling hand gesture database for natural user interface", GW 2011: the 9th International Gesture in Embodied Communication and Human-Computer InteractionWorkshop, 2011.
49. Głomb, P., M. Romaszewski, A. Sochan, and S. Opozda, "Unsupervised Parameter Selection for Gesture Recognition with Vector Quantization and Hidden Markov Models", Lecture Notes in Computer Science, Human-Computer Interaction – INTERACT, vol. 6949, 2011.
50. Romaszewski, M., and P. Głomb, "The Effect of Multiple Training Sequences on HMM Classification of Motion Capture Gesture Data", Computer Recognition Systems, vol. 4: Springer, pp. 365–373, 2011.

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