Source: http://ro.utia.cz/?q=publications
Timestamp: 2019-04-24 18:08:46+00:00

Document:
12. Pavel Mrázek, J. Weickert, A. Bruhn: On robust estimation and smoothing with spatial and tonal kernels. Geometric properties for incomplete data, 335-352. Springer, Berlin 2006.
13. Pavel Pudil, Jana Novovičová, Petr Somol: Recent feature selection methods in statistical pattern recognition. Pattern Recognition and String Matching, 1-51. Kluwer, Dordrecht 2003.
14. Jiří Grim: Pravděpodobnostní neuronové sítě. Umělá inteligence (4), 276-312. Academia, Praha 2003.
15. Michal Haindl: Model-based pattern recognition. Pattern Recognition and String Matching, 201-236. Kluwer, Dordrecht 2003.
16. Michal Haindl, Stanislava Šimberová: Model-based restoration of short-exposure solar images. Frontiers in Artificial Intelligence and Applications. 87. Soft Computing Systems Design, Management and Applications, 697-706. IOS Press, Amsterdam 2002.
17. Jiří Grim, Pavel Boček, Pavel Pudil: Interaktivní prezentace výsledků sčítání lidu pomocí pravděpodobnostních modelů se zaručenou ochranou anonymity dat. Manažerské rozhledy FM 2001. Sborník příspěvků, 13-18. VŠE, Jindřichův Hradec 2002.
18. Pavel Pudil, Z. Říhová: Učící se metody rozpoznávání a jejich použití v ekonomii a managementu. Manažerské rozhledy FM 2000. Sborník příspěvků FM JU, 81-90. VŠE, Praha 2001.
19. K. Haindl, Michal Haindl: Aeration at hydraulic structures. Developments in Hydraulic Engineering - 2, 95-134. Gihodo, Tokyo 2001.
20. Pavel Pudil: Multidisciplinární podpora managementu. Vědecký sborník VŠE v Praze. University of Economics, Prague 2000.
21. Jana Novovičová: Pravděpodobnost a matematická statistika. ČVUT, Praha 1999.
22. Pavel Pudil, Jana Novovičová: Novel methods for feature subset selection with respect to problem knowledge. Feature Extraction, Construction and Selection: A Data Mining Perspective, 101-116. Kluwer Academic, Boston 1998.
23. Jana Novovičová, Pavel Pudil: Feature selection and classification by modified model with latent structure. Dealing with Complexity. A Neural Networks Approach, 126-138. Springer, London 1997.
24. Michal Haindl, Stanislava Šimberová: A regression model contribution to astronomical image reconstruction. Data Analysis in Astronomy, 303-310. World Scientific, Singapore 1997.
25. D. Kovanicová, Pavel Kovanic: Poklady skryté v účetnictví. Díl 1,2. Polygon, Praha 1995.
39. Jiří Grim, Petr Somol, Michal Haindl, J. Daneš: Computer-Aided Evaluation of Screening Mammograms Based on Local Texture Models. IEEE Transactions on Image Processing 18:4 (2009), 765-773.
45. Jiří Grim, Jan Hora: Iterative principles of recognition in probabilistic neural networks. Neural Networks 21:6 (2008), 838-846. Elsevier.
47. Michal Haindl, Stanislav Mikeš: Unsupervised Texture Segmentation Using Multiple Segmenters Strategy. Lecture Notes in Computer Science 4472 (2007), 210-219.
48. Jana Novovičová, Petr Somol, Michal Haindl, Pavel Pudil: Conditional Mutual Information Based Feature Selection for Classification Task. Lecture Notes in Computer Science 45:4756 (2007), 417-426.
51. Petr Somol, Jana Novovičová, Pavel Pudil: Notes on the evolution of feature selection methodology. Kybernetika 43:5 (2007), 713-730. Ústav teorie informace a automatizace AV ČR, v. v. i..
53. Jiří Grim, Jan Hora: Minimum Information Loss Cluster Analysis for Cathegorical Data. Lecture Notes in Computer Science 2007, 233-247.
55. Jiří Grim: Neuromorphic features of probabilistic neural networks. Kybernetika 43:5 (2007), 697-712. Ústav teorie informace a automatizace AV ČR, v. v. i..
57. Jana Novovičová, Petr Somol, Pavel Pudil: Oscillating feature subset search algorithm for text categorization. Lecture Notes in Computer Science 44:4225 (2006), 578-587.
60. Stanislav Mikeš, Michal Haindl: Prague texture segmentation data generator and benchmark. ERCIM News 64 (2006), 67-68.
61. Jiří Grim: EM cluster analysis for categorical data. Lecture Notes in Computer Science 44:4109 (2006), 640-648.
67. Jana Novovičová: Text document classification. ERCIM News, 53-54.
68. M. Svítek, Jana Novovičová: Performance parameters definition and processing. Neural Network World 15:6 (2005), 1-11. Ústav informatiky AV ČR, v. v. i..
69. Michal Haindl, Stanislav Mikeš: Colour texture segmentation using modelling approach. Pattern Recognition and Image Analysis 3687:- (2005), 484-491.
70. Michal Haindl, Stanislava Šimberová: Restoration of multitemporal short-exposure astronomical images. Proceedings of the 14th Scandinavian Conference on Image Analysis. SCIA 2005 3540.
71. Jiří Grim, Petr Somol, Pavel Pudil: Probabilistic neural network playing and learning Tic-Tac-Toe. Pattern Recognition Letters 26:12 (2005), 1866-1873. Elsevier.
72. Michal Haindl, Jiří Filip: Modelling of authentic reflectance behaviour in virtual environments. ERCIM News, 49-50.
73. Petr Somol, Pavel Pudil, J. Kittler: Fast Branch & Bound algorithms for optimal feature selection. IEEE Transactions on Pattern Analysis and Machine Intelligence 26:7 (2004), 900-912.
74. Jiří Grim, J. Hora, Pavel Pudil: Interaktivní reprodukce výsledků sčítání lidu pomocí statistického modelu se zaručenou ochranou anonymity dat. Statistika 40:5 (2004), 400-414.
75. Jana Novovičová, Antonín Malík: Text document classification based on mixture models. Kybernetika 40:3 (2004), 293-304. Ústav teorie informace a automatizace AV ČR, v. v. i..
76. Jiří Grim, Michal Haindl: Texture modelling by discrete distribution mixtures. Computational Statistics and Data Analysis 41, 603-615. Elsevier.
77. Jiří Grim, P. Just, Pavel Pudil: Strictly modular probabilistic neural networks for pattern recognition. Neural Network World 13:6 (2003), 599-615. Ústav informatiky AV ČR, v. v. i..
79. Jiří Grim, J. Kittler, Pavel Pudil, Petr Somol: Multiple classifier fusion in probabilistic neural networks. Pattern Analysis and Applications 5:7 (2002), 221-233.
80. Pavel Pudil, Jana Novovičová, Petr Somol: Feature selection toolbox software package. Pattern Recognition Letters 23:4 (2002), 487-492. Elsevier.
82. Pavel Pudil, Michal Haindl: Czech Pattern Recognition Society. IAPR Newsletter 23:3 (2001), 4-5.
83. Michal Haindl, P. Slavík: Image-based acquisition of virtual gallery model. ERCIM News, 15.
85. Michal Haindl, Vojtěch Havlíček: Colour texture modelling. ERCIM News, 23-24.
86. Petr Somol, Pavel Pudil: Branch & Bound algoritmus s částečným řazením uzlů výpočetního stromu. Acta Oeconomica Pragensia 8:2 (2000), 33-40.
87. Petr Somol, Pavel Pudil: Oscilační algoritmy pro vyhledávání příznaků. Acta Oeconomica Pragensia 8:2 (2000), 25-32.
88. Pavel Pudil, P. Pirožek, Petr Somol: Výběr nejinformativnějších faktorů při akvizici podniků pomocí metod rozpoznávání obrazů. Acta Oeconomica Pragensia 8:2 (2000), 143-159.
89. Pavel Pudil, Jana Novovičová, Petr Somol: Znalostní přístup k výběru nejinformativnějších proměnných pro rozhodovací problémy klasifikačního typu. Acta Oeconomica Pragensia 8:2 (2000), 11-24.
90. Pavel Paclík, Jana Novovičová, Pavel Pudil, Petr Somol: Road sing classification using Laplace kernel classifier. Pattern Recognition Letters 21, 1165-1173. Elsevier.
91. Jiří Grim, Pavel Pudil, Petr Somol: Probabilistic information retrieval from census data based on distribution mixtures. Acta Oeconomica Pragensia 8:2 (2000), 41-47.
92. Jiří Grim: Self-organizing maps and probabilistic neural networks. Neural Network World 10:3 (2000), 407-415. Ústav informatiky AV ČR, v. v. i..
93. K. Fuka, Pavel Pudil: Objektová analýza a návrh systému pro podporu rozhodování. Výsledky a zhodnocení. Acta Oeconomica Pragensia 8:2 (2000), 60-70.
95. Jiří Grim, J. Vejvalková: An iterative inference mechanism for the probabilistic expert system PES. International Journal of General Systems 27, 373-396.
96. Pavel Pudil, M. Paterson: Improving the quality of decision-making in health care management: A project report from the Nevada/Bohemia health management education partnership. Journal of Health Administration Education 16:2 (1998), 255-262.
97. Pavel Pudil, Jana Novovičová: Novel methods for subset selection with respect to problem knowledge. IEEE Intelligent Systems 13:2 (1998), 66-74.
98. Igor Vajda, Jiří Grim: About the maximum information and maximum likelihood principles in neural networks. Kybernetika 34:4 (1998), 485-494. Ústav teorie informace a automatizace AV ČR, v. v. i..
99. Pavel Pudil, Jana Novovičová, Petr Somol, Radislav Vrňata: Conceptual base of feature selection consulting system. Kybernetika 34:4 (1998), 451-460. Ústav teorie informace a automatizace AV ČR, v. v. i..
100. Michal Haindl, Stanislava Šimberová: A scratch removal method. Kybernetika 34:4 (1998), 423-428. Ústav teorie informace a automatizace AV ČR, v. v. i..
101. Jiří Grim: Mixture of experts architectures for neural networks as a special case of conditional expectation formula. Kybernetika 34:4 (1998), 417-422. Ústav teorie informace a automatizace AV ČR, v. v. i..
102. Z. Říhová, Pavel Pudil: Šíření a využívání informací z hlediska participativního rozhodování. Acta Oeconomica Pragensia 5:1 (1997), 93-101.
103. Pavel Pudil, Michal Haindl: Statistical techniques in pattern recognition. ERCIM News, 57.
105. P. Andris, J. P. Costeira, K. Dobrovodský, Michal Haindl, J. Kittler, P. Kurdel, J. Santos-Victor, A. J. Stoddart: VIRTUOUS. ERCIM News, 25.
106. Jana Novovičová, Pavel Pudil, J. Kittler: Divergence based feature selection for multimodal class densities. IEEE Transactions on Pattern Analysis and Machine Intelligence 18:1 (1996), 218-223.
107. Michal Haindl: IAPR on the Network!. IAPR Newsletter 18:1 (1996), 5.
108. Michal Haindl, Stanislava Šimberová: A high - resolution radiospectrograph image reconstruction method. . Astronomy and Astrophysics Supplement Series 115, 189-193.
109. Michal Haindl: HIT Browser. ERCIM News, 12.
110. Michal Haindl: A new multimedia synchronization model. IEEE Journal on Selected Areas in Communications 14:1 (1996), 73-83.
111. Pavel Pudil, Jana Novovičová, N. Choakjarernwanit, J. Kittler: Feature selection based on the approximation of class densities by finite mixtures of special type. Pattern Recognition 28:9 (1995), 1389-1398. Elsevier.
112. Michal Haindl, M. M. de Ruiter: The MADE help system. Computer Graphics Forum 14:3 (1995), 149-157.
32. Zdeněk Wagner, Pavel Kovanic: Advanced Data Analysis for Industrial Applications. Abstracts Book, 5. -, - 2015.
84. Stanislava Šimberová, Michal Haindl, Jan Flusser: Mathematics improves astronomical image understanding. Mathematics and Astronomy: A joint Long Journey, 215-221. American Institute of Physics, Melville 2010.
95. Jana Novovičová, Petr Somol, Pavel Pudil: A New Measure of Feature Selection Algorithms’ Stability. ICDMW '09: Proceedings of the 2009 IEEE International Conference on Data Mining Workshops, 382-387. IEEE Computer Society, Washington, DC, USA 2009.
97. Petr Somol, Jiří Grim, Pavel Pudil: Criteria Ensembles in Feature Selection. Multiple Classifier Systems, LNCS 5519, 304-313. Springer, Berlin Heidelberg 2009.
116. Jiří Grim: Extraction of Binary Features by Probabilistic Neural Networks. Artificial Neural Networks - ICANN 2008, 52-61. Springer, Berlin 2008.
120. G. Scarpa, Michal Haindl, J. Zerubia: A Hierarchical Finite-State Model for Texture Segmentation. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'07) /32./, 1209-1212. IEEE, Los Alamos 2007.
124. Michal Haindl, Stanislava Šimberová: Validation of Classical and Blind Criteria for Image Quality Evaluation. Proceedings of the Ninth IASTED International Conference on Signal and Image Processing, 218-223. ACTA Press, Anaheim 2007.
125. Jan Hora: Informational Cathegorical Data Clustering. Doktorandské dny 2007, 57-66. Česká technika ČVUT, Praha 2007.
127. Jiří Grim, Jan Hora: Recurrent Bayesian Reasoning in Probabilistic Neural Networks. Artificial Neural Networks - ICANN 2007, 129-138. Springer, Berlin 2007.
128. Martin Hatka: Syntéza periodicko-stochastických textur. Doktorandské dny 2007, 39-48. Česká technika ČVUT, Praha 2007.
130. P. Paclík, Jana Novovičová, R.P.W. Duin: A trainable similarity measure for image classification. Proceedings of the 18th Conference on Pattern Recognition. ICPR 2006, 391-394. IEEE, Los Alamitos 2006.
131. Pavel Pudil, Petr Somol, Michal Haindl: Introduction to Statistical Pattern Recognition. MATEO - The European Network of Mechatronics Centres and Industrial Controllers 2006, 163-170. West Bohemian University, Pilsen, Plzeň 2006.
134. Michal Haindl, Pavel Pudil, Petr Somol: Pattern Recognition Based on Multidimensional Models. MATEO - The European Network of Mechatronics Centres and Industrial Controllers 2006, 80-86. West Bohemian University, Pilsen, Plzeň 2006.
135. Jiří Grim, Michal Haindl, Petr Somol, Pavel Pudil: A subspace approach to texture modelling by using Gaussian mixtures. Proceedings of the 18th Conference on Pattern Recognition. ICPR 2006, 235-238. IEEE, Los Alamitos 2006.
139. Pavel Pudil, Petr Somol: Current feature selection techniques in pattern recognition. Advances in Soft Computing. . Proceedings of the 4th International Conference on Computer Recognition Systems, 53-68. Springer, Heidelberg 2005.
140. Pavel Pudil, Petr Somol: An overview of feature selection techniques in statistical pattern recognition. Proceedings of the Sixtheenth Annual Symposium of the Pattern Recognition Association of South Africa, 1-14. University of Cape Town, Cape Town 2005.
142. Jana Novovičová, Antonín Malík: Information-theoretic feature selection algorithms for text classification. Proceedings of the International Joint Conference on Neural Networks, 3272-3277. IEEE Computational Intelligence Society, Los Alamitos 2005.
143. Pavel Vácha: Texture similarity measure. WDS'05 Proceedings of Contributed Papers, 47-52. MATFYZPRESS, Praha 2005.
144. Michal Haindl, M. Hatka: BTF Roller. Texture 2005. Proceedings of the 4th International Workshop on Texture Analysis, 89-94. IEEE, Los Alamitos 2005.
145. Michal Haindl, M. Hatka: A roller - fast sampling-based texture synthesis algorithm. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision. WSCG 2005. Proceedings, 80-83. University of West Bohemia, Plzen 2005.
146. Jiří Grim, Petr Somol, Michal Haindl, Pavel Pudil: A statistical approach to local evalution of a single texture image. Proceedings of the Sixtheenth Annual Symposium of the Pattern Recognition Association of South Africa, 171-176. University of Cape Town, Cape Town 2005.
147. Jiří Filip, Michal Haindl: Efficient image-based Bidirectional Texture Function model. Texture 2005. Proceedings of the 4th International Workshop on Texture Analysis, 7-12. IEEE, Los Alamitos 2005.
148. Michal Haindl, Jiří Grim, Pavel Pudil, M. Kudo: A hybrid BTF model based on Gaussian mixtures. Texture 2005. Proceedings of the 4th International Workshop on Texture Analysis, 95-100. IEEE, Los Alamitos 2005.
149. Michal Haindl, Stanislava Šimberová: Probabilistic model-based restoration of short-exposure astronomical images. Signal and Image Processing. Proceedings, 619-624. Acta Press, Anaheim 2004.
150. Jana Novovičová, Antonín Malík, Pavel Pudil: Feature selection using improved mutual information for text classification. Structural, Syntactic, and Statistical Pattern Recognition. Joint IAPR International Workshops SSPR 2004 and SPR 2004. Proceedings, 1010-1017. Springer, Berlin 2004.
152. Michal Haindl, Jiří Filip, M. Arnold: BTF image space utmost compression and modelling method. Proceedings of the 17th IAPR International Conference on Pattern Recognition, 194-197. IEEE, Los Alamitos 2004.
153. Michal Haindl, Stanislav Mikeš: Model-based texture segmentation. Image Analysis and Recognition. Proceedings, 306-313. Springer, Berlin 2004.
154. Jiří Filip, Michal Haindl: Non-linear reflectance model for Bidirectional Texture Function synthesis. Proceedings of the 17th IAPR International Conference on Pattern Recognition, 80-83. IEEE, Los Alamitos 2004.
155. Jiří Grim, J. Hora, Pavel Boček, Petr Somol, P. Pudil: Information analysis of census data by using statistical models. Proceedings of the International Conference on Statistics - Investment in the Future, 1-7. Czech Statistical Office, Prague 2004.
156. Michal Haindl, Jiří Filip: A fast probabilistic Bidirectional Texture Function model. Image Analysis and Recognition, 298-305. Springer, Heidelberg 2004.
157. Michal Haindl, Jiří Grim, Petr Somol, Pavel Pudil, M. Kudo: A Gaussian mixture-based colour texture model. Proceedings of the 17th IAPR International Conference on Pattern Recognition, 177-180. IEEE, Los Alamitos 2004.
158. Jana Novovičová, Antonín Malík: Application of multinomial mixture model to text classification. Lecture Notes in Computer Science. 2652. Pattern Recognition and Image Analysis, 646-653. Springer, Berlin 2003.
159. Jana Novovičová, Antonín Malík: Application of finite mixtures to text document classification. Znalosti 2003. Sborník příspěvků 2. ročníku konference, 23-32. VŠB, Ostrava 2003.
160. Michal Haindl, Jiří Filip: Fast BTF texture modelling. Texture 2003. Proceedings, 47-52. IEEE Press, Edinburgh 2003.
161. Stanislav Mikeš, Michal Haindl: Multispectral texture segmentation. WDS '03 Proceedings of Contributed Papers, 221-225. MFF UK, Praha 2003.
162. Jiří Grim, Petr Somol, Pavel Pudil, P. Just: Probabilistic neural network playing a simple game. Artificial Neural Networks in Pattern Recognition. Proceedings, 132-138. University of Florence, Florence 2003.
163. Michal Haindl, Jiří Filip: Fast restoration of colour movie scratches. Proceedings of the 16th International Conference on Pattern Recognition, 269-272. IEEE Computer Society, Los Alamitos 2002.
164. Michal Haindl, H. Lauschmann: Model-based fatigue fractographs texture analysis. Lecture Notes in Computer Science. 2396. Structural, Syntactic, and Statistical Pattern Recognition. Proceedings, 842-849. Springer, Berlin 2002.
165. Michal Haindl, Vojtěch Havlíček: A simple multispectral multiresolution Markov texture model. Texture 2002. The 2nd International Workshop on Texture Analysis and Synthesis, 63-66. HeriotWatt University, Glasgow 2002.
166. Michal Haindl: Recursive model-based colour image restoration. Lecture Notes in Computer Science. 2396. Structural, Syntactic, and Statistical Pattern Recognition. Proceedings, 617-626. Springer, Berlin 2002.
167. Michal Haindl, Vojtěch Havlíček: A multiscale colour texture model. Proceedings of the 16th International Conference on Pattern Recognition, 255-258. IEEE Computer Society, Los Alamitos 2002.
168. Jiří Grim, Michal Haindl: A discrete mixtures colour texture model. Texture 2002. The 2nd International Workshop on Texture Analysis and Synthesis, 59-62. HeriotWatt University, Glasgow 2002.
170. Pavel Pudil, Petr Somol: Recent advances in methodology of feature selection for statistical pattern recognition. Computer Data Analysis and Modeling. Proceedings of the Sixth International Conference, 163-171. Belarussian State University, Minsk 2001.
172. P. Paclík, Jana Novovičová: Number of components and initialization in Gaussian mixture model for pattern recognition. Artificial Neural Nets and Genetic Algorithms. Proceedings, 406-409. Springer, Wien 2001.
174. Jiří Grim, J. Kittler, Pavel Pudil, Petr Somol: Information analysis of multiple classifier fusion. Lecture Notes in Computer Science. 2096. Multiple Classifier Systems, 168-177. Springer, Berlin 2001.
175. Jiří Grim, Pavel Boček, Pavel Pudil: Safe dissemination of census results by means of interactive probabilistic models. Proceedings of the ETK-NTTS 2001 Conference, 849-856. European Communities, Rome 2001.
176. J. Kittler, Pavel Pudil, Petr Somol: Advances in statistical feature selection. Lecture Notes in Computer Science. 2013. Advances in Pattern Recognition - ICAPR 2001. Proceedings, 425-434. Springer, Heidelberg 2001.
177. M. Kudo, Petr Somol, Pavel Pudil, M. Shimbo, J. Sklansky: Comparison of classifier-specific feature selection algorithms. Lecture Notes in Computer Science. 1876. Advances in Pattern Recognition, 677-686. Springer, Berlin 2000.
178. Michal Haindl: Texture modelling. Computer Science and Engineering. 7. Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, 634-639. International Institute of Informatics and Systemics, Orlando 2000.
179. H. Mayer, Petr Somol: Conventional and evolutionary feature selection of SAR data using a filter approach. Proceedings of SCI 2000. The 4th World Multiconference on Systemics, Cybernetics and Informatics, 427-433. IIIS, Orlando 2000.
180. Michal Haindl, Š. Kment, P. Slavík: Virtual information systems. Proceedings of the 8th International Conference in Central Europe on Computer Graphics, Visualization and Interactive Digital Media '2000, 22-27. University of West Bohemia, Plzeň 2000.
181. P. Paclík, Jana Novovičová: Road sign classification without color information. Proceedings of the 6th Annual Conference of the Advanced School for Computing and Imaging (ASCI), 84-90. Technische Universiteit, Delft 2000.
184. H. Mayer, Petr Somol, R. Huber, Pavel Pudil: Improving statistical measures of feature subsets by conventional and evolutionary approaches. Lecture Notes in Computer Science. 1876. Advances in Pattern Recognition. Proceedings, 77-86. Springer, Berlin 2000.
185. Michal Haindl: Recursive square-root filters. Proceedings of the 15th IAPR International Conference on Pattern Recognition, 1018-1021. IEEE Computer Society, Los Alamitos 2000.
186. Jiří Grim, J. Kittler, Pavel Pudil, Petr Somol: Combining multiple classifiers in probabilistic neural networks. Lecture Notes in Computer Science. 1857. Multiple Classifier Systems, 157-166. Springer, Berlin 2000.
187. Michal Haindl: Recursive model-based image restoration. Proceedings of the 15th IAPR International Conference on Pattern Recognition, 346-349. IEEE Computer Society, Los Alamitos 2000.
189. Jiří Grim, Pavel Pudil, Petr Somol: Multivariate structural Bernoulli mixtures for recognition of handwritten numerals. Proceedings of the 15th International Conference on Pattern Recognition, 585-589. IEEE Computer Society, Los Alamitos 2000.
190. Michal Haindl, Vojtěch Havlíček: A multiresolution causal colour texture model. Lecture Notes in Computer Science. 1876. Advances in Pattern Recognition. Proceedings, 114-122. Springer, Berlin 2000.
191. Michal Haindl, Vojtěch Havlíček, Pavel Žid: Automatic acquisition of planar-faced virtual models. Proceedings of the 15th IAPR International Conference on Pattern Recognition, 987-990. IEEE Computer Society, Los Alamitos 2000.
192. Michal Haindl: Edge preserving model-based image restoration. Proceedings of the Czech Pattern Recognition Workshop 2000, 49-54. Czech Pattern Recognition Society, Praha 2000.
193. Pavel Pudil, Jana Novovičová, Petr Somol: Knowledge based feature selection in statistical pattern recognition. International Symposium on Pattern Recognition. "In Memoriam Pierre Devijver", 129-134. Royal Military Academy, Brussels 1999.
194. Pavel Pudil, K. Fuka, K. Beránek, P. Dvořák: Potential of artificial intelligence based feature selection methods in regression models. Proceedings of the Third International Conference on Computational Intelligence and Multimedia Applications 1999, 159-163. IEEE Computer Society Press, Los Alamitos 1999.
195. Pavel Pudil, K. Fuka, K. Beránek, P. Dvořák: Use of floating search methods in regression models. Proceedings of the 17th International Conference on Mathematical Methods in Economics '99, 219-224. VŠE, Praha 1999.
196. Pavel Paclík, Jana Novovičová, Pavel Pudil, Petr Somol: Road sign classification using the Laplace kernel classifier. Proceedings of the 11th Scandinavian Conference on Image Analysis, 275-282. Pattern Recognition Society Denmark, Lyngby 1999.
197. Michal Haindl: Texture segmentation using recursive Markov random field parameter estimation. Proceedings of the 11th Scandinavian Conference on Image Analysis, 771-776. Pattern Recognition Society of Denmark, Lyngby 1999.
199. Jiří Grim: Information approach to structural optimization of probabilistic neural networks. Fourth European Congress on Systems Science, 527-539. SESGE, Valencia 1999.
200. Jiří Grim, Pavel Pudil: Interactive presentation of socio-economic databases by means of probabilistic models. Proceedings of the 17th International Conference on Mathematical Methods in Economics '99, 103-108. VŠE, Praha 1999.
201. Jana Novovičová: Approximation of Bayes classifier using t-mixtures. Preprints of the 3rd European IEEE Workshop on Computer-Intensive Methods in Control and Data Processing, 247-252. ÚTIA AV ČR, Praha 1998.
202. Michal Haindl: Unsupervised texture segmentation. Lecture Notes in Computer Science. 1451. Advances in Pattern Recognition. Proceedings, 1021-1028. Springer, Berlin 1998.
203. Pavel Pudil, Jana Novovičová, Petr Somol, Radislav Vrňata: Feature selection expert - user oriented approach. Methodology and concept of the system. Lecture Notes in Computer Science. 1451. Advances in Pattern Recognition. Proceedings, 573-582. Springer, Berlin 1998.
204. Pavel Pudil: Využití učících se metod rozpoznávání pro podporu rozhodování v klinické praxi i ve zdravotní péči. Systémy na podporu rozhodování ve zdravotnictví, -. FM VŠE, Jindřichův Hradec 1998.
205. Michal Haindl, Pavel Žid: Range image segmentation by curve grouping. Proceedings of the 7th International Workshop on Robotics in Alpe-Adria-Danube Region, 339-344. ASCO Art, Bratislava 1998.
206. Pavel Pudil: Management znalostí. Systémy na podporu rozhodování ve zdravotnictví, -. FM VŠE, Jindřichův Hradec 1998.
207. Jiří Grim, Jana Novovičová, Pavel Pudil, Petr Somol, F. J. Ferri: Initializing normal mixtures of densities. Proceedings of the 14th International Conference on Pattern Recognition, 886-890. IEEE, Los Alamitos 1998.
209. Michal Haindl, Vojtěch Havlíček: Multiresolution colour texture synthesis. Proceedings of the 7th International Workshop on Robotics in Alpe-Adria-Danube Region, 297-302. ASCO Art, Bratislava 1998.
210. Jiří Grim, Pavel Pudil: On virtually binary nature of probabilistic neural networks. Lecture Notes in Computer Science. 1451. Advances in Pattern Recognition. Proceedings, 765-774. Springer, Berlin 1998.
211. Michal Haindl, Pavel Žid: Fast segmentation of plannar surfaces in range images. Proceedings of the 14th International Conference on Pattern Recognition, 985-987. IEEE, Los Alamitos 1998.
212. Michal Haindl, Vojtěch Havlíček: Colour texture modelling. Week of Doctoral Students 1998. Proceedings, 128-135. Matfyzpress, Praha 1998.
213. Pavel Pudil, Jana Novovičová, Petr Somol, Radislav Vrňata: User oriented approach to feature selection in statistical pattern recognition. Multidisciplinární přístupy k podpoře rozhodování v ekonomii a managementu. Workshop '97 grantu VS 96063, 15-26. Fakulta managementu JU, Jindřichův Hradec 1997.
214. Pavel Pudil, Z. Říhová: Potential of floating search methods for managing redundant information. Proceedings of the 4th Interdisciplinary Information Management Talks, 72-81. R.Oldenbourg, München 1997.
215. Pavel Pudil, K. Fuka, J. Plešingr, Petr Somol, Radislav Vrňata: Vize a koncepce výstupu z projektu "Multidisciplinární přístupy k podpoře rozhodování v ekonomii a managementu". Multidisciplinární přístupy k podpoře rozhodování v ekonomii a managementu. Workshop '97 - Grant VS 96063, 41-49. FM JU, Jindřichův Hradec 1997.
216. Igor Vajda, Jiří Grim: About the maximum information and maximum likelihood principles in neural networks. Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, 189-197. ÚTIA AV ČR, Praha 1997.
217. Pavel Pudil, Z. Říhová: Participativní rozhodování z hlediska chování manažérů a distribuce informací. Vybrané výsledky mezinárodní studie. Manažerské rozhledy '96. Sborník prací FM JU, 33-34. FM JU, Jindřichův Hradec 1997.
218. Petr Somol: Different approaches to initialization of the EM algorithm for use in Gaussian mixture modelling methods. Multidisciplinární přístupy k podpoře rozhodování v ekonomii a managementu. Workshop '97 grantu VS 96063, 85-91. Fakulta managementu JU, Jindřichův Hradec 1997.
219. Z. Říhová, Pavel Pudil: Manažérské chování z hlediska participativního rozhodování. Vybrané výsledky mezinárodní studie. Systémové přístupy '96. Sborník, 105-112. VŠE, Praha 1997.
220. Michal Haindl, Pavel Žid: A range image segmentation method. Czech Pattern Recognition Workshop '97. Proceedings, 69-76. Czech Pattern Recognition Society, Praha 1997.
222. Pavel Pudil, Jana Novovičová, Petr Somol, Radislav Vrňata: Conceptual base of feature selection consulting system. Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, 125-134. ÚTIA AV ČR, Praha 1997.
223. Michal Haindl, Stanislava Šimberová: A scratch removal method. Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, 61-66. ÚTIA AV ČR, Praha 1997.
224. Michal Haindl, Pavel Žid: A range image segmentation method. Week of Doctoral Students 1997. Proceedings, 115-121. MFF UK, Praha 1997.
225. J. Kittler, A. J. Stoddart, J. Santos-Victor, J. P. Costeira, Michal Haindl, K. Dobrovodský, P. Andris, P. Kurdel: Virtuous: Autonomous acquisition of virtual reality models from real world scenes. International Workshop on Robotics in Alpe-Adria-Danube Region, 487-492. Studio 22 Edizion, Cassino 1997.
226. Michal Haindl, Pavel Žid: Fast segmentation of range images. Lecture Notes in Computer Science. 1310. Images Analysis and Processing, 295-302. Springer, Berlin 1997.
227. Pavel Pudil, Jana Novovičová, F. J. Ferri: New tools for knowledge guided approach to feature selection in statistical pattern recognition. Intelligent Feature Selection: Statistical and Neural Approaches, 1-4. University of Sussex, Brighton 1996.
228. Pavel Pudil, Z. Říhová: Potential of floating search methods for managing redundant information. IDIMT '96. 4th Interdisciplinary Information Management Talks. Proceedings, 72-81. R.Oldenbourg, München 1996.
229. Michal Haindl, Stanislava Šimberová: Adaptive reconstruction method of multispectral images. International Archives of Photogrammetry and Remote Sensing, 809-814. ISPRS, Vienna 1996.
230. Jana Novovičová, Pavel Pudil, Petr Somol: Feature selection in statistical pattern recognition via modified model with latent structure. Computer-Intensive Methods in Control and Signal Processing. Preprints of the 2nd European IEEE Workshop CMP'96, 217-222. ÚTIA AV ČR, Praha 1996.
231. Jiří Grim, Pavel Boček: Statistical model of Prague households for interactive presentation of census data. SoftStat '95. Advances in Statistical Software 5, 271-278. Lucius & Lucius, Stuttgart 1996.
233. F. J. Ferri, J. Albert, I. Gracia, F. Pla, Pavel Pudil, Jana Novovičová: Hierarchical feature selection: A decision tree based approach. Intelligent Feature Selection: Statistical and Neural Approaches, 7-8. University of Sussex, Brighton 1996.
234. Jiří Grim: Maximum-likelihood design of layered neural networks. International Conference on Pattern Recognition. Proceedings, 85-89. IEEE Computer Society Press, Los Alamitos 1996.
235. Zdeněk Vostrý, Jiří Záworka: Heat dynamics in gas transport. Proceedings of the SIMONE Congress '95, 64-75. LIWACOM, Essen 1995.
236. Zdeněk Vostrý, T. Jeníček: State reconstruction for gas networks. Proceedings of the SIMONE Congress '95, 18-33. LIWACOM, Essen 1995.
237. Jiří Záworka: Survey on SIMONE achievements to date and development trends. Proceedings of the SIMONE Congress '95, 1-12. LIWACOM, Essen 1995.
238. Zdeněk Vostrý: Estimation of quality tracking accuracy for billing purposes. Proceedings of the SIMONE Congress '95, 34-43. LIWACOM, Essen 1995.
239. Pavel Kolář: Regulární celulární systémy pro simulaci chování biologických buněčných tkání. Computer Science, 229-235. Technical University, Ostrava 1995.
240. Michal Haindl, Stanislava Šimberová: A multi-model image line reconstruction. Lecture Notes in Computer Science. 970. Computer Analysis of Image and Patterns, 735-740. Springer, Berlin 1995.
241. T. Jeníček, Zdeněk Vostrý, Jiří Záworka: Future SIMONE developments in optimum control. Proceedings of the SIMONE Congress '95, 82-93. LIWACOM, Essen 1995.
242. Jana Novovičová, Pavel Pudil, J. Kittler: Feature selection based on divergence for empirical class densities. Proceedings of the 9th Scandinavian Conference on Image Analysis, 989-996. SSAB, Uppsala 1995.
243. Pavel Pudil, Jana Novovičová, F. J. Ferri, J. Kittler: Advances in the statistical methodology for the selection of image descriptors for visual pattern representation and classification. Lecture Notes in Computer Science. 970. Computer Analysis of Images and Patterns, 832-837. Springer, Berlin 1995.
7. Jiří Filip: Towards Effective Measurement and Interpolation of Bidirectional Texture Functions. Research Report 2298. ÚTIA AV ČR, v.v.i, Praha 2011.
9. Petr Somol, Pavel Pudil: Sequential Retreating Search Methods in Feature Selection. Research Report 2286. ÚTIA, Praha 2010.
11. Pavel Vácha: Query by Pictorial Example. MFF UK, Praha 2010.
12. Petr Somol, Jana Novovičová, Pavel Pudil, J. Kittler: Feature Selection - A Very Compact Survey Over the Diversity of Existing Approaches. Research Report 2285. ÚTIA AV ČR, v.v.i, Praha 2010.
13. Michal Haindl: ERCIM News no.80 - Digital Preservation. 2010.
14. Stanislav Mikeš: Image Segmentation. MFF UK, Praha 2010.
16. Petr Somol, Jana Novovičová: Evaluating Stability of Single and Multiple Feature Selectors that Optimize Feature Subset Cardinality. Research Report 2251. ÚTIA AV ČR, Praha 2009.
17. Michal Haindl: ERCIM News no. 77 - 79. 2009.
18. Michal Haindl: ERCIM News (no. 72-75). 2008.
19. Jiří Grim, Petr Somol: Diagnostic Enhancement of Screening Mammograms by Means of Local Texture Models. Research Report 2217. ÚTIA AV ČR, Praha 2008.
20. Petr Somol, Jana Novovičová: Does It Make Sense to Develop New Feature Selection Methods?. Research Report 2193. ÚTIA AV ČR, Praha 2007.
21. Pavel Pudil, Petr Somol, Michal Haindl: Selection of Most Informative Variables in Statistical Pattern Recognition. MATEO -The European Network of Mechatronics Centres and Industrial Controllers . UWB, Plzeň 2007.
22. Michal Haindl, Pavel Pudil, Petr Somol: Model-Based Visual Inspection. MATEO - The European Network of Mechatronics Centres and Industrial Controllers . UWB, Plzeň 2007.
23. Michal Haindl, Petr Somol: Statistical Analysis of Medical Images and Its Possible Impact on Medical Practice. International Conference Efficiency, Quality and Consumer Satisfaction in Healthcare and Welfare, 1-1. STAPRO, Praha 2007.
24. Michal Haindl, Stanislava Šimberová: Probabilistic suppression of astronomical degradations. Proceedings of Abstracts of Modern Solar Facilities - Advanced Solar Science, 1-1. Universitätsverlag Göttingen, Göttingen 2007.
25. Petr Somol, Jana Novovičová, Pavel Pudil: Advances in Feature Selection Methodology: an Overview of Recent ÚTIA Results. Interní publikace - DAR - ÚTIA 2006/21. ÚTIA AV ČR, Praha 2006.
27. Jiří Grim: Neuromorphic Features of Probabilistic Neural Networks. Interní publikace - DAR - ÚTIA 2006/20. ÚTIA AV ČR, Praha 2006.
28. Jiří Humpolíček: Text document classification. Research Report 2175. ÚTIA AV ČR, Praha 2006.
29. J. Meseth, P. Degener, R. Klein, Michal Haindl, Jiří Filip, Petr Somol: Texture Synthesis on Surfaces. Research Report 2141. ÚTIA AV ČR, Praha 2005.
30. Petr Somol, Michal Haindl: Novel Path Search Algorithm for Image Stitching and Advanced Texture Tiling. ÚTIA AV ČR, Praha 2005.
31. Michal Haindl, Jiří Filip, Petr Somol: Texturing Library - Reference Manual. Research Report 2142. ÚTIA AV ČR, Praha 2005.
32. Michal Haindl, Stanislava Šimberová: Restoration of Multitemporal Short-Exposure Astronomical Images. ÚTIA AV ČR, Praha 2005.
33. Michal Haindl, M. Hatka: A Roller - Fast Sampling-Based Texture Synthesis Algorithm. ÚTIA AV ČR, Praha 2005.
34. Jiří Filip: Colour Rough Textures Modelling. Ph.D. Thesis. ÚTIA AV ČR, Praha 2005.
35. Petr Somol, Michal Haindl: Texture Tiling and Patching with a Novel Path Search Algorithm for Quick and Realistic Texture Synthesis. Research Report 2122. ÚTIA AV ČR, Praha 2004.
36. Pavel Žid: Range Image Segmentation. Ph.D. Thesis. 2004.
37. Michal Haindl, Jiří Filip, Petr Somol, Vojtěch Havlíček: RealReflect Library - Reference Manual. Research Report 2121. ÚTIA AV ČR, Praha 2004.
38. J. Meseth, G. Müller, R. Klein, Michal Haindl, Jiří Filip, Petr Somol, Pavel Žid: Specification and Prototype Description of Texture Mapping and Synthesis. Research Report 2107. ÚTIA AV ČR, Praha 2004.
39. Michal Haindl, Jiří Filip, Petr Somol: Advances in BTF Modelling. Research Report 2119. ÚTIA AV ČR, Praha 2004.
40. Antonín Malík: Mixture models for learning text document classifiers. Abstract. Proceedings of the 4th International PhD Workshop Information Technologies & Control. Young Generation Viewpoint, 6. ÚTIA AV ČR, Praha 2003.
41. Vojtěch Havlíček: Colour Texture Modelling. Ph.D. Thesis. 2003.
42. Michal Haindl, Jiří Filip, Petr Somol, J. Meseth: BTF Parametric Database. Research Report 2090. ÚTIA AV ČR, Praha 2003.
43. Michal Haindl, R. Klein, Jiří Filip, Petr Somol, J. Meseth: Specification and Prototype Description of BTF Database and Model. Research Report 2076. ÚTIA AV ČR, Praha 2003.
45. Michal Haindl, Jiří Filip, Petr Somol: Specification and Prototype Description of Texture Model. Research Report 2075. ÚTIA AV ČR, Praha 2002.
46. Michal Haindl: Markovian Image Models. Habilitation Thesis. 2001.
47. Jana Novovičová: Statistical Pattern Recognition: Methods for Feature Selection. Habilitation Thesis. 2001.
48. Jiří Grim: The models of conditional independence: Finite mixtures of product components and their application. Abstract. Recent Developments in Mixture Modelling. Abstracts, 59. Universität der Bundeswehr, Hamburg 2001.
49. Michal Haindl, J. Filip: A Fast Model-Based Restoration of Colour Movie Scratches. Research Report 2031. ÚTIA AV ČR, Praha 2001.
50. Jiří Grim, Michal Haindl: A Monospectral Probabilistic Discrete Mixture Texture Model. Research Report 2018. ÚTIA AV ČR, Praha 2001.
51. Jiří Grim: Latent Structure Analysis for Categorical Data. Research Report 2019. ÚTIA AV ČR, Praha 2001.
52. Jiří Grim, Michal Haindl: A mixture-based colour texture model. Abstract. Recent Developments in Mixture Modelling. Abstracts, 58. Universität der Bundeswehr, Hamburg 2001.
53. Petr Somol: Algoritmy a programová realizace řešení problémů redukce vysoké dimenzionality vstupních dat ve statistickém rozpoznávání obrazů. Doktorská disertační práce. 2000.
54. Michal Haindl: Recursive Square-Root Filters. Research Report 1980. ÚTIA AV ČR, Praha 2000.
55. Michal Haindl, Vojtěch Havlíček: Texture Mapping II. Research Report 1962. ÚTIA AV ČR, Praha 1999.
56. Michal Haindl, Vojtěch Havlíček: Texture Synthesis II. Research Report 1965. ÚTIA AV ČR, Praha 1999.
57. Michal Haindl, Vojtěch Havlíček, Pavel Žid: Shape and Texture Data Fusion II. Research Report 1958. ÚTIA AV ČR, Praha 1999.
58. Ivan Nagy, Miroslav Kárný, Jana Novovičová, Markéta Valečková: Mixture-model Identification in Traffic Control Problems. Research Report 1973. ÚTIA AV ČR, Praha 1999.
59. Miroslav Kárný, Ivan Nagy, Jana Novovičová: Quasi-Bayes Approach to Multi-Model Fault Detection and Isolation. Research Report 1974. ÚTIA AV ČR, Praha 1999.
60. Michal Haindl, Pavel Žid: Scene Segmentation III. Research Report 1966. ÚTIA AV ČR, Praha 1999.
61. Jiří Grim: Pravděpodobnostní neuronové sítě. Research Report 1953. ÚTIA AV ČR, Praha 1999.
62. Michal Haindl: Image Restoration. Research Report 1967. ÚTIA AV ČR, Praha 1999.
63. Michal Haindl: Markovian Image Models. DrSc. Dissertation. 1999.
64. Michal Haindl, Vojtěch Havlíček: Texture Synthesis. Research Report 1943. ÚTIA AV ČR, Praha 1998.
65. Michal Haindl: Texture Mapping. Research Report 1942. ÚTIA AV ČR, Praha 1998.
66. Michal Haindl, Pavel Žid: Scene Segmentation II. Research Report 1944. ÚTIA AV ČR, Praha 1998.
67. Michal Haindl: Shape and Texture Data Fusion. Research Report 1941. ÚTIA AV ČR, Praha 1998.
68. Michal Haindl, Pavel Žid: Scene Segmentation. Research Report 1940. ÚTIA AV ČR, Praha 1997.
69. Michail I. Schlesinger: Identifikacija statističeskich parametrov v odnoj modeli uslovnoj nezavisimosti. Research Report 1895. ÚTIA AV ČR, Praha 1997.
70. Michal Haindl, Vojtěch Havlíček: Texture Analysis. Research Report 1938. ÚTIA AV ČR, Praha 1997.
71. Michal Haindl, Vojtěch Havlíček: Prototype Implementation of the Texture Analysis Objects. Research Report 1939. ÚTIA AV ČR, Praha 1997.
73. Jana Novovičová: [Recenze]. IAPR Newsletter 18:3 (1996), 5.
74. Igor Vajda, Jiří Grim: On Information Theoretic Optimality of Radial Basis Function Neural Networks. Research Report 1864. ÚTIA AV ČR, Praha 1996.
75. Igor Vajda, Jiří Grim: About Optimality of Probabilistic Basic Function Neural Networks. Research Report 1887. ÚTIA AV ČR, Praha 1996.
76. Michal Haindl, Stanislav Saic: Automatická analýza kožních útvarů. Research Report 1871. ÚTIA AV ČR, Praha 1996.
77. Jiří Grim, D. Vavruška: Probabilistic Knowledge-based Models Defined by Finite Distribution Mixtures. Research Report 1873. ÚTIA AV ČR, Praha 1996.
78. Jiří Grim, J. Vejvalková: An Interative Inference Mechanism for the Probabilistic Expert System PES. Research Report 1866. ÚTIA AV ČR, Praha 1996.
79. Jiří Grim: An Alternative Design of Mixture of Experts Architectures for Neural Networks. Research Report 1883. ÚTIA AV ČR, Praha 1996.
80. Jiří Grim: Discretization in Probabilistic Neural Networks with Bounded Information Loss. Research Report 1878. ÚTIA AV ČR, Praha 1996.
81. Michal Haindl, M. M. de Ruiter: The MADE Help System. Research Report R9528. CWI, Amsterdam 1995.
82. Michal Haindl: Multimedia Synchronization. Research Report R9538. CWI, Amsterdam 1995.
83. Pavel Kovanic: Gnostická teorie neurčitých dat. Doktorská disertační práce. ÚTIA ČSAV, Praha 1990.
1. Michal Haindl: Multiple Classifier Systems.
2. Michal Haindl, J. Kittler, F. Roli: International Workshop on Multiple Classifier Systems /7./.
3. F. J. Ferri, J. M. Inesta, A. Amin, Pavel Pudil: Advances in Pattern Recognition. Lecture Notes in Computer Science. 1876. Springer, Berlin 2000.
4. A. Amin, D. Dori, Pavel Pudil, H. Freeman: Advances in Pattern Recognition. Proceedings. Lecture Notes in Computer Science. 1451. Springer, Berlin 1998.
5. Pavel Pudil, Jana Novovičová, Jiří Grim: Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition. ÚTIA AV ČR, Praha 1997.

References: v. 
 v. 
 v. 
 v. 
 v. 
 v. 
 v. 
 v. 
 v. 
 v.