Machine Learning Group

Group leader: 

Group members: 

2024

2023

Strzoda A, Grochla K, Głomb P, Madej A.  2023.  Link failure prediction in LoRa networks. International Wireless Communications and Mobile Computing Conference, IWCMC.
Gardas B, Głomb P, Sadowski P, Puchała Z, Jałowiecki K, Pawela Ł, Faucoz O, Brunet P-M, Gawron P, Van Waveren M et al..  2023.  Hyper-Spectral Image Classification Using Adiabatic Quantum Computation. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium.
Głomb P, Romaszewski M, Cholewa M, Koral W, Madej A, Skrabski M, Kołodziej K.  2023.  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..
Głomb P, Cholewa M, Foszner P, Bularz J.  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, FedCSIS 2023, Warsaw, Poland, September 17-20, 2023.

2022

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

2021

2020

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)

2019

2018

2017

2016

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.
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.
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.

2015

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

2014

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.
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.

2013

2012

Blachnik M., Głomb P.  2012.  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. :477–485.
Głomb P, Romaszewski M, Opozda S, Sochan A.  2012.  Choosing and Modeling the Hand Gesture Database for a Natural User Interface. Gesture and Sign Language in Human-Computer Interaction and Embodied Communication.

2011

Sochan A, Głomb P, Skabek K, Romaszewski M, Opozda S.  2011.  Virtual Museum as an Example of 3D Content Distribution in the Architecture of a Future Internet. Computer Networks 2011. Communications in Computer and Information Science 160.. :459–464.
Gawron P, Głomb P, Miszczak J, Puchała Z.  2011.  Eigengestures for natural human computer interface. Man-Machine Interactions 2. :49–56.
Cholewa M, Głomb P.  2011.  Gesture data modeling and classification based on critical points approximation. Advances in Intelligent and Soft Computing, 2011, Volume 95, Computer Recognition Systems 4,. 95:365–373.
Głomb P, Romaszewski M, Opozda S, Sochan A.  2011.  Choosing and modeling hand gesture database for natural user interface. GW 2011: the 9th International Gesture in Embodied Communication and Human-Computer InteractionWorkshop.
Głomb P, Romaszewski M, Sochan A, Opozda S.  2011.  Unsupervised Parameter Selection for Gesture Recognition with Vector Quantization and Hidden Markov Models. Lecture Notes in Computer Science, Human-Computer Interaction – INTERACT. 6949

2010

2009

Romaszewski M, Głomb P.  2009.  3D Mesh Approximation Using Vector Quantization. Advances in Soft Computing. 57/2009:71–78.
Romaszewski M, Opozda S, Głomb P.  2009.  3D Mesh Identification Using Random Walks and Hidden Markov Models. Image Processing & Communications Challenges. :302–308.
Domańska J, Głomb P, Kowalski P, Nowak S.  2009.  Modeling of Internet 3D Traffic Using Hidden Markov Models. Advances in Intelligent and Soft Computing. 64
Głomb P, Nowak S.  2009.  IMAGE CODING WITH CONTOURLET / WAVELET TRANSFORMS AND SPIHT ALGORITHM:AN EXPERIMENTAL STUDY. proc. of IMAGAPP 2009, International Conference on Imaging Theory and Applications, Lisboa, Portugal, 2009..
Głomb P.  2009.  Detection of interest points on 3D data: extending the Harris operator. 6th International Conference on Computer Recognition Systems.

2008

Grochla K, Sochan A, Głomb P.  2008.  Transmission of scalable video streams. Proceedings from the 4th Euro-NGI Workshop on New trends in network architectures and services.

2007

Głomb P.  2007.  Image Language Terminal Symbols from Feature Analysis. IEEE International Workshop on Imaging Systems and Techniques – IST.

2006

2005

Głomb P, Grochla K.  2005.  Modeling Connection State with Kernel PCA. 2nd EuroNGI Workshop on New Trends in Modeling, Quantitative Methods and Measurements.

2004

2002

Historia zmian

Data aktualizacji: 05/04/2024 - 10:45; autor zmian: Łukasz Zimny (lzimny@iitis.pl)