Search results

  1. 1.
    0556464 - ÚTIA 2023 RIV CH eng M - Monography Chapter
    Haindl, Michal
    Bidirectional texture function modeling.
    Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging. Cham: Springer International Publishing, 2021 - (Chen, K.; Schonlieb, C.; Tai, X.; Younces, L.), s. 1-42. ISBN 978-3-030-03009-4
    R&D Projects: GA ČR(CZ) GA19-12340S
    Institutional support: RVO:67985556
    Keywords : Bidirectional Texture Function * Texture modeling * Markov random fields * Discrete distribution mixtures * EM algorithm
    OECD category: Robotics and automatic control
    http://library.utia.cas.cz/separaty/2022/RO/haindl-0556464.pdf
    Permanent Link: http://hdl.handle.net/11104/0330843
     
     
  2. 2.
    0497831 - ÚTIA 2019 RIV US eng M - Monography Chapter
    Grim, Jiří - Somol, Petr
    A Statistical Review of the MNIST Benchmark Data Problem.
    Advances in Pattern Recognition Research. New York: Nova Science Publishers, Inc., 2018 - (Lu, T.; Chao, T.), s. 172-193. ISBN 978-1-53614-429-1
    R&D Projects: GA ČR GA17-18407S
    Institutional support: RVO:67985556
    Keywords : MNIST benchmark * multivariate Bernoulli mixtures * EM algorithm
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    http://library.utia.cas.cz/separaty/2018/RO/grim-0497831.pdf
    Permanent Link: http://hdl.handle.net/11104/0290648
     
     
  3. 3.
    0484891 - ÚI 2018 GB eng J - Journal Article
    Štepánová, K. - Vavrečka, Michal
    Estimating number of components in Gaussian mixture model using combination of greedy and merging algorithm.
    Pattern Analysis and Applications. Roč. 21, č. 1 (2018), s. 181-192. ISSN 1433-7541. E-ISSN 1433-755X
    Keywords : Clustering * EM algorithm * Gaussian mixture model * Mixture model * Number of clusters
    Impact factor: 1.410, year: 2018
    Permanent Link: http://hdl.handle.net/11104/0280014
     
     
  4. 4.
    0475182 - ÚTIA 2018 RIV GB eng J - Journal Article
    Grim, Jiří
    Approximation of Unknown Multivariate Probability Distributions by Using Mixtures of Product Components: A Tutorial.
    International Journal of Pattern Recognition and Artificial Intelligence. Roč. 31, č. 9 (2017), č. článku 1750028. ISSN 0218-0014. E-ISSN 1793-6381
    R&D Projects: GA ČR GA17-18407S
    Institutional support: RVO:67985556
    Keywords : multivariate statistics * product mixtures * naive Bayes models * EM algorithm * pattern recognition * neural networks * expert systems * image analysis
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 1.029, year: 2017
    http://library.utia.cas.cz/separaty/2017/RO/grim-0475182.pdf
    Permanent Link: http://hdl.handle.net/11104/0272087
     
     
  5. 5.
    0464681 - ÚTIA 2017 RIV CZ eng C - Conference Paper (international conference)
    Grim, Jiří
    Feasibility Study of an Interactive Medical Diagnostic Wikipedia.
    SPMS 2016 Stochastic and Physical Monitoring Systems. Prague: Czech Technical University, 2016, s. 31-45. ISBN 978-80-01-06040-7.
    [SPMS 2016 Stochastic and Physical Monitoring Systems. Prague - Dobřichovice (CZ), 20.06.2016-24.06.2016]
    R&D Projects: GA ČR(CZ) GA14-02652S; GA ČR(CZ) GA14-10911S
    Institutional support: RVO:67985556
    Keywords : Multivariate statistics * Medical diagnostics * Product mixtures * Incomplete data * Sequential classification * EM algorithm
    Subject RIV: IN - Informatics, Computer Science
    http://library.utia.cas.cz/separaty/2016/RO/grim-0464681.pdf
    Permanent Link: http://hdl.handle.net/11104/0263972
     
     
  6. 6.
    0452538 - ÚTIA 2016 RIV CH eng C - Conference Paper (international conference)
    Grim, Jiří - Pudil, P.
    Mixtures of Product Components versus Mixtures of Dependence Trees.
    Computational Intelligence. Cham: Springer, 2016, s. 365-382. Studies in Computational Intelligence, 620. ISBN 978-3-319-26393-9.
    [IJCCI 2014 - International Joint Conference on Computational Intelligence (Rome/Italy). Rome (IT), 22.10.2014-24.10.2014]
    R&D Projects: GA ČR(CZ) GA14-02652S
    Grant - others: GA ČR(CZ) GAP403/12/1557
    Institutional support: RVO:67985556
    Keywords : Product mixtures * Mixtures of Dependence Trees * EM algorithm
    Subject RIV: BD - Theory of Information
    http://library.utia.cas.cz/separaty/2016/RO/grim-0452538.pdf
    Permanent Link: http://hdl.handle.net/11104/0257056
     
     
  7. 7.
    0435901 - ÚTIA 2015 RIV CZ eng C - Conference Paper (international conference)
    Grim, Jiří
    Approximating Probability Densities by Mixtures of Gaussian Dependence Trees.
    Stochastic and Physical Monitoring Systems, SPMS 2014. Praha: ČVUT, 2014. ISBN 978-80-01-05616-5.
    [Stochastic and Physical Monitoring Systems SPMS 2014. Malá Skála (CZ), 23.06.2014-28.06.2014]
    R&D Projects: GA ČR(CZ) GA14-02652S; GA ČR(CZ) GA14-10911S
    Institutional support: RVO:67985556
    Keywords : Multivariate statistics * Mixtures of dependence trees * EM algorithm * Pattern recognition * Medical image analysis
    Subject RIV: IN - Informatics, Computer Science
    http://library.utia.cas.cz/separaty/2014/RO/grim-0435901.pdf
    Permanent Link: http://hdl.handle.net/11104/0241872
     
     
  8. 8.
    0434119 - ÚTIA 2015 RIV PT eng C - Conference Paper (international conference)
    Grim, Jiří - Pudil, P.
    Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees.
    NCTA2014 - International Conference on Neural Computation Theory and Applications. Rome: SCITEPRESS, 2014, s. 65-75. ISBN 978-989-758-054-3.
    [6-th International Conference on Neural Computation Theory and Applications. Rome (IT), 22.10.2014-24.10.2014]
    R&D Projects: GA ČR(CZ) GA14-02652S
    Grant - others: GA ČR(CZ) GAP403/12/1557
    Institutional support: RVO:67985556
    Keywords : Probabilistic Neural Networks * Product Mixtures * Mixtures of Dependence Trees * EM Algorithm
    Subject RIV: IN - Informatics, Computer Science
    http://library.utia.cas.cz/separaty/2014/RO/grim-0434119.pdf
    Permanent Link: http://hdl.handle.net/11104/0238366
     
     
  9. 9.
    0428565 - ÚTIA 2015 RIV GB eng J - Journal Article
    Grim, Jiří
    Sequential pattern recognition by maximum conditional informativity.
    Pattern Recognition Letters. Roč. 45, č. 1 (2014), s. 39-45. ISSN 0167-8655. E-ISSN 1872-7344
    R&D Projects: GA ČR(CZ) GA14-02652S; GA ČR(CZ) GA14-10911S
    Keywords : Multivariate statistics * Statistical pattern recognition * Sequential decision making * Product mixtures * EM algorithm * Shannon information
    Subject RIV: IN - Informatics, Computer Science
    Impact factor: 1.551, year: 2014
    http://library.utia.cas.cz/separaty/2014/RO/grim-0428565.pdf
    Permanent Link: http://hdl.handle.net/11104/0234221
     
     
  10. 10.
    0411134 - UTIA-B 20030121 RIV IT eng C - Conference Paper (international conference)
    Grim, Jiří - Somol, Petr - Pudil, Pavel - Just, P.
    Probabilistic neural network playing a simple game.
    Florence: University of Florence, 2003. In: Artificial Neural Networks in Pattern Recognition. Proceedings. - (Marinai, S.; Gori, M.), s. 132-138
    [IAPR TC3 Workshop 2003 /1./. Florence (IT), 12.09.2003-13.09.2003]
    R&D Projects: GA ČR GA402/01/0981; GA ČR GA402/03/1310; GA AV ČR KSK1019101
    Institutional research plan: CEZ:AV0Z1075907
    Keywords : probabilistic neural networks * finite mixtures * EM algorithm
    Subject RIV: BB - Applied Statistics, Operational Research
    Permanent Link: http://hdl.handle.net/11104/0131221