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Filters: Autor is Przemysław Głomb [Clear All Filters]
Effective transfer learning for hyperspectral image classification with deep convolutional neural networks.. 2019.
A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification. IEEE Geoscience and Remote Sensing Letters. 16:467-471.. 2019.
Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data. Computer and Information Sciences.. 2018.
Application of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns. Forensic Science International. 290. 2018.
Automatic pigment identification from hyperspectral data. Journal of Cultural Heritage. 31:1-12.. 2018.
Quantum hidden Markov models based on transition operation matrices. Quantum Information Processing. 16:101.. 2017.
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.
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.
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.. 2016.
Two Stage SVM Classification for Hyperspectral Data. Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM.. 2016.
Classification of LPG clients using the Hurst exponent and the correlation coeficient. Theoretical and Applied Informatics. 27(1):13–24.. 2015.
Experimental Evaluation of Selected Approaches to Covariance Matrix Regularization. Artificial Intelligence and Soft Computing. 9120:391-401.. 2015.
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.. 2014.
Surface Mixture Models for the Optimization of Object Boundary Representation. Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science 8467. :703–714.. 2014.
Aplikacje Sieci Świadomej Treści. Inżynieria Internetu przyszłości część 2.. 2013.
Aplikacje sieci świadomej treści. Przegląd telekomunikacyjny. :1491–1502.. 2012.
Choosing and Modeling the Hand Gesture Database for a Natural User Interface. Gesture and Sign Language in Human-Computer Interaction and Embodied Communication.. 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.. 2012.
Choosing and modeling hand gesture database for natural user interface. GW 2011: the 9th International Gesture in Embodied Communication and Human-Computer InteractionWorkshop.. 2011.
The Effect of Multiple Training Sequences on HMM Classification of Motion Capture Gesture Data. Computer Recognition Systems. 4:365–373.. 2011.
Eigengestures for natural human computer interface. Man-Machine Interactions 2. :49–56.. 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.. 2011.