J. Grim

Michal Haindl, Jirí Grim, Vojtech Havlícek, 2010, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).

EM Cluster Analysis for Categorical Data

Jirí Grim, J. Grim, 2006, SSPR/SPR.

Neuromorphic features of probabilistic neural networks

Jirí Grim, J. Grim, 2007, Kybernetika.

Probabilistic mixture-based image modelling

Michal Haindl, Jirí Grim, Vojtech Havlícek, 2011, Kybernetika.

Probabilistic Discrete Mixtures Colour Texture Models

Michal Haindl, Jirí Grim, Vojtech Havlícek, 2008, CIARP.

Fast dependency-aware feature selection in very-high-dimensional pattern recognition

Pavel Pudil, Petr Somol, Jirí Grim, 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

Statistical Model of the 2001 Czech Census for Interactive Presentation

Pavel Pudil, Petr Somol, Pavel Bocek, 2010 .

Mixture of experts architectures for neural networks as a special case of conditional expectation formula

Jirí Grim, J. Grim, 1998, Kybernetika.

Minimum Information Loss Cluster Analysis for Categorical Data

Jirí Grim, Jan Hora, J. Grim, 2007, MLDM.

Multiple Classifier Fusion in Probabilistic Neural Networks

Josef Kittler, Pavel Pudil, Petr Somol, 2002, Pattern Analysis & Applications.

Multivariate structural Bernoulli mixtures for recognition of handwritten numerals

Pavel Pudil, Petr Somol, Jirí Grim, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

RECOGNITION OF HANDWRITTEN NUMERALS BY STRUCTURAL PROBABILISTIC NEURAL NETWORKS

Pavel Pudil, Petr Somol, Jǐŕı Grim, 2008 .

On numerical evaluation of maximum-likelihood estimates for finite mixtures of distributions

Jirí Grim, J. Grim, 1982, Kybernetika.

Recognition of Properties by Probabilistic Neural Networks

Jirí Grim, Jan Hora, J. Grim, 2009, ICANN.

Extraction of Binary Features by Probabilistic Neural Networks

Jirí Grim, J. Grim, 2008, ICANN.

Iterative principles of recognition in probabilistic neural networks.

Jirí Grim, Jan Hora, J. Grim, 2008, Neural networks : the official journal of the International Neural Network Society.

Approximation of Unknown Multivariate Probability Distributions by Using Mixtures of Product Components: A Tutorial

Jirí Grim, J. Grim, 2017, Int. J. Pattern Recognit. Artif. Intell..

Computational Properties of Probabilistic Neural Networks

Jirí Grim, Jan Hora, J. Grim, 2010, ICANN.

Computer-Aided Evaluation of Screening Mammograms Based on Local Texture Models

Petr Somol, Michal Haindl, Jirí Grim, 2009, IEEE Transactions on Image Processing.

Recurrent Bayesian Reasoning in Probabilistic Neural Networks

Jirí Grim, Jan Hora, J. Grim, 2007, ICANN.

Color Texture Segmentation by Decomposition of Gaussian Mixture Model

Pavel Pudil, Petr Somol, Michal Haindl, 2006, CIARP.

A Subspace Approach to Texture Modelling by Using Gaussian Mixtures

Pavel Pudil, Petr Somol, Michal Haindl, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

On Stopping Rules in Dependency-Aware Feature Ranking

Jirí Filip, Pavel Pudil, Petr Somol, 2013, CIARP.

Mixtures of Product Components Versus Mixtures of Dependence Trees

Pavel Pudil, Jirí Grim, P. Pudil, 2014, IJCCI.

Texture Defect Detection

Michal Haindl, Stanislav Mikes, Jirí Grim, 2007, CAIP.

Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees

Pavel Pudil, Jirí Grim, P. Pudil, 2014, IJCCI.

Texture modelling by discrete distribution mixtures

Michal Haindl, Jirí Grim, M. Haindl, 2003, Comput. Stat. Data Anal..

Safe Dissemination of Census Results by Means of Interactive Probabilistic Models

Pavel Pudil, Pavel Bocek, Jir ´ i Grim, 2001 .

Multivariate statistical pattern recognition with nonreduced dimensionality

Jirí Grim, J. Grim, 1986, Kybernetika.

Boosting in probabilistic neural networks

Pavel Pudil, Petr Somol, Jirí Grim, 2002, Object recognition supported by user interaction for service robots.