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Przemyslaw Glomb
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2020 – today
- 2024
- [j7]Kamil Ksiazek
, Wilhelm Masarczyk
Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data. Comput. Biol. Medicine 176: 108544 (2024) - [c23]Piotr Gawron, Przemyslaw Sadowski, Przemyslaw Glomb, Bartlomiej Gardas, Matthijs van Waveren, Clément Forray, Guillaume Pasero, Mickaël Savinaud, Pierre-Marie Brunet, Orphee Faucoz, Zbigniew Puchala, Lukasz Pawela:
What Could be Achieved with a Million Qubits Quantum Annealer in Remote Sensing? IGARSS 2024: 475-478 - [i12]Michal Romaszewski, Przemyslaw Sekula, Przemyslaw Glomb, Michal Cholewa, Katarzyna Kolodziej:
Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models. CoRR abs/2406.04926 (2024) - [i11]Michal Cholewa, Michal Romaszewski, Przemyslaw Glomb, Katarzyna Kolodziej, Michal Gorawski, Jakub Koral, Wojciech Koral, Andrzej Madej, Kryspin Musiol:
'Just One More Sensor is Enough' - Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors. CoRR abs/2406.19900 (2024) - [i10]Katarzyna Kolodziej, Michal Cholewa, Przemyslaw Glomb, Wojciech Koral, Michal Romaszewski:
Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials. CoRR abs/2410.02772 (2024) - 2023
- [c22]Przemyslaw Glomb, Michal Cholewa, Pawel Foszner, Jakub Bularz:
Continual learning of a time series model using a mixture of HMMs with application to the IoT fuel sensor verification. FedCSIS 2023: 259-264 - [c21]Bartlomiej Gardas, Przemyslaw Glomb, Przemyslaw Sadowski, Zbigniew Puchala, Konrad Jalowiecki, Lukasz Pawela, Orphee Faucoz, Pierre-Marie Brunet, Piotr Gawron
Hyper-Spectral Image Classification Using Adiabatic Quantum Computation. IGARSS 2023: 620-623 - [c20]Krisztián Búza, Kamil Ksiazek, Wilhelm Masarczyk, Przemyslaw Glomb, Piotr Gorczyca
A Simple and Effective Classifier for the Detection of Schizophrenia and Bipolar Disorder based on Heart Rate Variability Time Series. ITAT 2023: 217-222 - [c19]Anna Strzoda, Krzysztof Grochla, Przemyslaw Glomb, Andrzej Madej:
Link failure prediction in LoRa networks. IWCMC 2023: 1310-1315 - 2022
- [j6]Krzysztof Grochla
Energy-Aware Algorithm for Assignment of Relays in LP WAN. ACM Trans. Sens. Networks 18(4): 60:1-60:23 (2022) - [c18]Bartosz Grabowski
Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering. ACIIDS (Companion) 2022: 102-121 - [c17]Kamil Ksiazek
Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation. ICIAP (1) 2022: 391-403 - [i9]Bartosz Grabowski, Przemyslaw Glomb, Wojciech Masarczyk, Pawel Plawiak, Özal Yildirim, U. Rajendra Acharya
Classification and Self-Supervised Regression of Arrhythmic ECG Signals Using Convolutional Neural Networks. CoRR abs/2210.14253 (2022) - 2021
- [i8]Kamil Ksiazek
Stable training of autoencoders for hyperspectral unmixing. CoRR abs/2109.13748 (2021) - [i7]Michal Cholewa, Michal Romaszewski, Przemyslaw Glomb:
Heuristical choice of SVM parameters. CoRR abs/2111.02164 (2021) - 2020
- [j5]Wojciech Masarczyk
Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling. Remote. Sens. 12(16): 2653 (2020) - [j4]Kamil Ksiazek
Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks. Sensors 20(22): 6666 (2020) - [i6]Michal Romaszewski, Przemyslaw Glomb, Arkadiusz Sochan, Michal Cholewa:
A Dataset for Evaluating Blood Detection in Hyperspectral Images. CoRR abs/2008.10254 (2020)
2010 – 2019
- 2019
- [j3]Michal Cholewa
A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification. IEEE Geosci. Remote. Sens. Lett. 16(3): 467-471 (2019) - [i5]Wojciech Masarczyk, Przemyslaw Glomb, Bartosz Grabowski, Mateusz Ostaszewski
Effective transfer learning for hyperspectral image classification with deep convolutional neural networks. CoRR abs/1909.05507 (2019) - 2018
- [c16]Michal Romaszewski
Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data. ISCIS 2018: 113-120 - [i4]Przemyslaw Glomb, Krzysztof Domino, Michal Romaszewski, Michal Cholewa:
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images. CoRR abs/1808.03513 (2018) - 2017
- [j2]Michal Cholewa
Quantum hidden Markov models based on transition operation matrices. Quantum Inf. Process. 16(4): 101 (2017) - 2016
- [c15]Michal Cholewa, Przemyslaw Glomb:
Two Stage SVM Classification for Hyperspectral Data. ICPRAM 2016: 387-391 - [c14]Michal Romaszewski, Przemyslaw Glomb
Parameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences. VISIGRAPP (3: VISAPP) 2016: 140-147 - [c13]Przemyslaw Glomb
Performance of Interest Point Descriptors on Hyperspectral Images. VISIGRAPP (3: VISAPP) 2016: 200-205 - 2015
- [c12]Michal Cholewa
Natural human gestures classification using multisensor data. ACPR 2015: 499-503 - [c11]Przemyslaw Glomb
Experimental Evaluation of Selected Approaches to Covariance Matrix Regularization. ICAISC 2015: 391-401 - 2014
- [c10]Przemyslaw Glomb
Surface Mixture Models for the Optimization of Object Boundary Representation. ICAISC (1) 2014: 703-714 - [c9]Przemyslaw Sporysz, Przemyslaw Glomb
Improving the quality of mesh simplification with texture saliency measurement. IPTA 2014: 117-122 - [c8]Michal Romaszewski
Natural hand gestures for human identification in a Human-Computer Interface. IPTA 2014: 404-409 - 2013
- [j1]Michal Cholewa
Estimation of the number of states for gesture recognition with Hidden Markov Models based on the number of critical points in time sequence. Pattern Recognit. Lett. 34(5): 574-579 (2013) - 2012
- [c7]Marcin Blachnik
Do We Need Complex Models for Gestures? A Comparison of Data Representation and Preprocessing Methods for Hand Gesture Recognition. ICAISC (1) 2012: 477-485 - 2011
- [c6]Arkadiusz Sochan, Przemyslaw Glomb
Virtual Museum as an Example of 3D Content Distribution in the Architecture of a Future Internet. CN 2011: 459-464 - [c5]Przemyslaw Glomb
Choosing and Modeling the Hand Gesture Database for a Natural User Interface. Gesture Workshop 2011: 24-35 - [c4]Piotr Gawron
Eigengestures for Natural Human Computer Interface. ICMMI 2011: 49-56 - [c3]Przemyslaw Glomb
Unsupervised Parameter Selection for Gesture Recognition with Vector Quantization and Hidden Markov Models. INTERACT (4) 2011: 170-177 - [p5]Michal Cholewa, Przemyslaw Glomb:
Gesture Data Modeling and Classification Based on Critical Points Approximation. Computer Recognition Systems 4 2011: 307-315 - [p4]Michal Romaszewski, Przemyslaw Glomb:
The Effect of Multiple Training Sequences on HMM Classification of Motion Capture Gesture Data. Computer Recognition Systems 4 2011: 365-373 - [i3]Piotr Gawron, Przemyslaw Glomb, Jaroslaw Adam Miszczak, Zbigniew Puchala:
Eigengestures for natural human computer interface. CoRR abs/1105.1293 (2011) - [i2]Michal Romaszewski, Piotr Gawron, Przemyslaw Glomb:
Towards a natural gesture interface: LDA-based gesture separability. CoRR abs/1109.5034 (2011) - [i1]Michal Cholewa, Przemyslaw Glomb:
Deciding of HMM parameters based on number of critical points for gesture recognition from motion capture data. CoRR abs/1110.6287 (2011)
2000 – 2009
- 2009
- [c2]Slawomir Nowak, Przemyslaw Glomb:
Image Coding with Contourlet/Wavelet Transforms and SPIHT Algorithm - An Experimental Study. IMAGAPP 2009: 37-42 - [p3]Michal Romaszewski, Przemyslaw Glomb:
3D Mesh Approximation Using Vector Quantization. Computer Recognition Systems 3 2009: 71-78 - [p2]Przemyslaw Glomb:
Detection of Interest Points on 3D Data: Extending the Harris Operator. Computer Recognition Systems 3 2009: 103-111 - 2008
- [p1]Przemyslaw Glomb
Local Analysis of Stereo Image Pairs with Polynomial Series. Computer Recognition Systems 2 2008: 117-123 - 2005
- [c1]Przemyslaw Glomb:
Analysis of fGn and http Requests Traces Using Localized Multiscale H Parameter Estimation. SAINT Workshops 2005: 288-291
Coauthor Index
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