Grochla K, Strzoda A, Marjasz R, Głomb P, Książek K, Łaskarzewski Z.  2022.  Energy-Aware Algorithm for Assignment of Relays in LPWAN. Transactions on Sensor Networks. 18(4)

Książek K, Głomb P, Romaszewski M, Cholewa M, Grabowski B, Buza K.  2022.  Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation. 21st International Conference on Image Analysis and Processing. 13231

Grabowski B, Głomb P, Książek K, Buza K.  2022.   Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering. Asian Conference on Intelligent Information and Database Systems. 1716

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

Głomb P, Romaszewski M.  2020.  Anomaly detection in hyperspectral remote sensing images. Hyperspectral Remote Sensing: Theory & Applications.

Książek K, Romaszewski M, Głomb P, Grabowski B, Cholewa M.  2020.  Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks. Sensors. 20(Recent Advances in Multi- and Hyperspectral Image Analysis)

Romaszewski M, Głomb P, Sochan A, Cholewa M.  2020.  A Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set].

Masarczyk W, Głomb P, Grabowski B, Ostaszewski M.  2020.  Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling. Remote Sensing. 12(16)

Głomb P, Domino K, Romaszewski M, Cholewa M.  2019.  Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images. PP-RAI'2019. :p.121.

Cholewa M, Głomb P, Romaszewski M.  2019.  A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification. IEEE Geoscience and Remote Sensing Letters. 16:467-471.

Grabowski B, Głomb P, Romaszewski M, Ostaszewski M.  2019.  Unsupervised deep learning approach to hyperspectral anomaly detection. PP-RAI'2019.

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

Głomb P, Romaszewski M, Cholewa M, Domino K.  2018.  Application of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns. Forensic Science International. 290

Grabowski B, Masarczyk W, Głomb P, Mendys A.  2018.  Automatic pigment identification from hyperspectral data. Journal of Cultural Heritage. 31:1-12.

Cholewa M, Gawron P, Głomb P, Kurzyk D.  2017.  Quantum hidden Markov models based on transition operation matrices. Quantum Information Processing. 16:101.

Romaszewski M, Głomb P.  2016.  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.

Głomb P, Cholewa M.  2016.  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.

Romaszewski M, Głomb P, Cholewa M.  2016.  Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach. ISPRS Journal of Photogrammetry and Remote Sensing. 121:60-76.

Cholewa M, Głomb P.  2016.  Two Stage SVM Classification for Hyperspectral Data. Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM.

Domino K, Głomb P, Łaskarzewski Z..  2015.  Classification of LPG clients using the Hurst exponent and the correlation coeficient. Theoretical and Applied Informatics. 27(1):13–24.

Głomb P, Cholewa M.  2015.  Experimental Evaluation of Selected Approaches to Covariance Matrix Regularization. Artificial Intelligence and Soft Computing. 9120:391-401.

Romaszewski M, Głomb P, Gawron P.  2014.  Natural hand gestures for human identification in a Human-Computer Interface. Image Processing Theory Tools and Applications (IPTA), 2014 4th International Conference on. :404–409.

Głomb P, Sochan A.  2014.  Surface Mixture Models for the Optimization of Object Boundary Representation. Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science 8467. :703–714.

Cholewa M, Głomb P, Opozda S, Romaszewski M, Sochan A, Kosiedowski M., Kuśmierek E., Bęben A., Krawiec P., Stroiński A..  2013.  Aplikacje Sieci Świadomej Treści. Inżynieria Internetu przyszłości część 2.

Kosiedowski M., Kuśmierek E., Stroiński A., Cholewa M, Głomb P, Opozda S, Romaszewski M, Sochan A, Bęben A., Krawiec P..  2012.  Aplikacje sieci świadomej treści. Przegląd telekomunikacyjny. :1491–1502.