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Pavel Paclík
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2010 – 2019
- 2011
- [j12]Viet Cuong Dinh, Raimund Leitner
, Pavel Paclík, Marco Loog, Robert P. W. Duin:
SEDMI: Saliency based edge detection in multispectral images. Image Vis. Comput. 29(8): 546-556 (2011) - 2010
- [j11]Thomas C. W. Landgrebe, Pavel Paclík:
The ROC skeleton for multiclass ROC estimation. Pattern Recognit. Lett. 31(9): 949-958 (2010) - [c23]Pavel Paclík, Carmen Lai, Thomas C. W. Landgrebe, Robert P. W. Duin:
ROC Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers. ICPR 2010: 2977-2980 - [c22]Thomas Karavides, K. Y. Esther Leung, Pavel Paclík, Emile A. Hendriks, Johan G. Bosch:
Database guided detection of anatomical landmark points in 3D images of the heart. ISBI 2010: 1089-1092 - [c21]Thomas Karavides, K. Y. Esther Leung, Pavel Paclík, Emile A. Hendriks, Johan G. Bosch:
Database guided detection of anatomical landmark points in 3D images of the heart. Image Processing 2010: 76234Q
2000 – 2009
- 2009
- [c20]Viet Cuong Dinh, Raimund Leitner
A Clustering Based Method for Edge Detection in Hyperspectral Images. SCIA 2009: 580-587 - [c19]Feifei Huo, Emile A. Hendriks, Pavel Paclík, Augustinus H. J. Oomes:
Markerless human motion capture and pose recognition. WIAMIS 2009: 13-16 - 2008
- [c18]Pavel Paclík, Carmen Lai, Jana Novovicová, Robert P. W. Duin:
Variance estimation for two-class and multi-class ROC analysis using operating point averaging. ICPR 2008: 1-4 - 2007
- [c17]Fabrice Colas, Pavel Paclík, Joost N. Kok, Pavel Brazdil
Does SVM Really Scale Up to Large Bag of Words Feature Spaces? IDA 2007: 296-307 - 2006
- [j10]Pavel Paclík, Raimund Leitner
A study on design of object sorting algorithms in the industrial application using hyperspectral imaging. J. Real Time Image Process. 1(2): 101-108 (2006) - [j9]Elzbieta Pekalska, Robert P. W. Duin, Pavel Paclík:
Prototype selection for dissimilarity-based classifiers. Pattern Recognit. 39(2): 189-208 (2006) - [j8]Thomas C. W. Landgrebe, David M. J. Tax, Pavel Paclík, Robert P. W. Duin:
The interaction between classification and reject performance for distance-based reject-option classifiers. Pattern Recognit. Lett. 27(8): 908-917 (2006) - [j7]Pavel Paclík, Jana Novovicová, Robert P. W. Duin:
Building Road-Sign Classifiers Using a Trainable Similarity Measure. IEEE Trans. Intell. Transp. Syst. 7(3): 309-321 (2006) - [c16]Thomas C. W. Landgrebe, Pavel Paclík, Robert P. W. Duin:
Precision-recall operating characteristic (P-ROC) curves in imprecise environments. ICPR (4) 2006: 123-127 - [c15]Pavel Paclík, Jana Novovicová, Robert P. W. Duin:
A Trainable Similarity Measure for Image Classification. ICPR (3) 2006: 391-394 - [c14]M. van Staalduinen, Jan C. A. van der Lubbe, Eric Backer, Pavel Paclík:
Paper Retrieval Based on Specific Paper Features: Chain and Laid Lines. MRCS 2006: 346-353 - [c13]Marina Skurichina, Serguei Verzakov, Pavel Paclík, Robert P. W. Duin:
Effectiveness of Spectral Band Selection/Extraction Techniques for Spectral Data. SSPR/SPR 2006: 541-550 - [c12]Serguei Verzakov, Pavel Paclík, Robert P. W. Duin:
Edge Detection in Hyperspectral Imaging: Multivariate Statistical Approaches. SSPR/SPR 2006: 551-559 - 2005
- [c11]Pavel Paclík, Thomas C. W. Landgrebe, David M. J. Tax, Robert P. W. Duin:
On Deriving the Second-Stage Training Set for Trainable Combiners. Multiple Classifier Systems 2005: 136-146 - [c10]Thomas C. W. Landgrebe, Pavel Paclík, David M. J. Tax, Robert P. W. Duin:
Optimising Two-Stage Recognition Systems. Multiple Classifier Systems 2005: 206-215 - [c9]Pavel Paclík, Serguei Verzakov, Robert P. W. Duin:
Improving the Maximum-Likelihood Co-occurrence Classifier: A Study on Classification of Inhomogeneous Rock Images. SCIA 2005: 998-1008 - [c8]Serguei Verzakov, Pavel Paclík, Robert P. W. Duin:
The Tangent Kernel Approach to Illumination-Robust Texture Classification. SCIA 2005: 1009-1016 - 2004
- [j6]Carmen Lai, David M. J. Tax, Robert P. W. Duin, Elzbieta Pekalska, Pavel Paclík:
A Study On Combining Image Representations For Image Classification And Retrieval. Int. J. Pattern Recognit. Artif. Intell. 18(5): 867-890 (2004) - [c7]Pavel Paclík, Serguei Verzakov, Robert P. W. Duin:
Multi-Class Extensions of the GLDB Feature Extraction Algorithm for Spectral Data. ICPR (4) 2004: 629-632 - [c6]Thomas C. W. Landgrebe, Pavel Paclík, David M. J. Tax, Serguei Verzakov, Robert P. W. Duin:
Cost-Based Classifier Evaluation for Imbalanced Problems. SSPR/SPR 2004: 762-770 - [c5]Serguei Verzakov, Pavel Paclík, Robert P. W. Duin:
Feature Shaving for Spectroscopic Data. SSPR/SPR 2004: 1026-1033 - [c4]Marina Skurichina, Pavel Paclík, Robert P. W. Duin, Diana de Veld, Henricus J. C. M. Sterenborg, Max J. H. Witje, Jan L. N. Roodenburg:
Selection/Extraction of Spectral Regions for Autofluorescence Spectra Measured in the Oral Cavity. SSPR/SPR 2004: 1096-1104 - 2003
- [j5]Pavel Paclík, Robert P. W. Duin, Geert M. P. van Kempen, Reinhard Kohlus:
Segmentation of multi-spectral images using the combined classifier approach. Image Vis. Comput. 21(6): 473-482 (2003) - [j4]Pavel Paclík, Robert P. W. Duin:
Dissimilarity-based classification of spectra: computational issues. Real Time Imaging 9(4): 237-244 (2003) - 2002
- [c3]Pavel Paclík, Robert P. W. Duin, Geert M. P. van Kempen, Reinhard Kohlus:
Supervised Segmentation of Textures in Backscatter Images. ICPR (2) 2002: 490-493 - [c2]Carmen Lai, David M. J. Tax, Robert P. W. Duin, Elzbieta Pekalska, Pavel Paclík:
On Combining One-Class Classifiers for Image Database Retrieval. Multiple Classifier Systems 2002: 212-221 - [c1]Pavel Paclík, Robert P. W. Duin, Geert M. P. van Kempen, Reinhard Kohlus:
On Feature Selection with Measurement Cost and Grouped Features. SSPR/SPR 2002: 461-469 - 2001
- [j3]Elzbieta Pekalska, Pavel Paclík, Robert P. W. Duin:
A Generalized Kernel Approach to Dissimilarity-based Classification. J. Mach. Learn. Res. 2: 175-211 (2001) - 2000
- [j2]Pavel Paclík, Jana Novovicová, Pavel Pudil
Road sign classification using Laplace kernel classifier. Pattern Recognit. Lett. 21(13-14): 1165-1173 (2000)
1990 – 1999
- 1999
- [j1]Petr Somol, Pavel Pudil
Adaptive floating search methods in feature selection. Pattern Recognit. Lett. 20(11-13): 1157-1163 (1999)
Coauthor Index
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