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Bibliography

GA19-12340S

  1. Haindl MichalBidirectional texture function modeling , Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging : Mathematical Imaging and Vision, p. 1023-1064 , Eds: Chen Ke, Schonlieb Carola-Bibiane, Tai Xue-Cheng, Younces Laurent [2023] Download DOI: 10.1007/978-3-030-98661-2_103

  1. Vácha Pavel, Haindl MichalTexture recognition under scale and illumination variations , Journal of Information and Telecommunication vol.8, 1 (2024), p. 130-148 [2024] Download Download DOI: 10.1080/24751839.2023.2265190
  2. Žid Pavel, Haindl Michal, Havlíček VojtěchGovernmental Anti-Covid Measures Effectiveness Detection , Procedia Computer Science vol.225, 1 (2023), p. 2922-2931, International Conference on Knowledge-Based and Intelligent Information & Engineering Systems 2023 (KES 2023) /27./, (Athens, GR, 20230906) [2023] Download Download DOI: 10.1016/j.procs.2023.10.285
  3. Mikeš Stanislav, Haindl MichalTexture Segmentation Benchmark , IEEE Transactions on Pattern Analysis and Machine Intelligence vol.44, 9 (2022), p. 5647-5663 [2022] Download Download DOI: 10.1109/TPAMI.2021.3075916
  4. Havlíček Michal, Haindl MichalTexture Spectral Similarity Criteria , IET Image Processing vol.13, 11 (2019), p. 1998-2007 [2019] Download Download DOI: 10.1049/iet-ipr.2019.0250

  1. Haindl Michal, Shaih N.Texture Quality Criteria Comparison , Proceedings of the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW 2023), IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2023 /48./, (Rhodes, GR, 20230604) [2023] Download DOI: 10.1109/ICASSPW59220.2023.10193606
  2. Havlíček Michal, Haindl MichalTexture Spectral Similarity Criteria Comparison , WSCG 2023 Proceedings - 31. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2023, p. 100-106, International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2023, WSCG 2023, /31./, (Plzen, CZ, 20230515) [2023] Download DOI: 10.24132/CSRN.3301.13
  3. Mikeš Stanislav, Haindl MichalOptimal Activation Function for Anisotropic BRDF Modeling , Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - GRAPP, p. 162-169 , Eds: Sousa A. Augusto, Bashford-Rogers Thomas, Bouatouch Kadi, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - GRAPP 2023 /18./, (Lisbon, PT, 20230219) [2023] Download DOI: 10.5220/0011616200003417
  4. Haindl Michal, Havlíček VojtěchBRDF Anisotropy Criterion , Intelligent Information and Database Systems, p. 434-444 , Eds: Nguyen Ngoc Thanh, Tran Tien Khoa, Tukayev Ualsher, Hong Tzung-Pei, Trawinski Bogdan, Szczerbicki Edward, Asian Conference on Intelligent Information and Database Systems (ACIIDS 2022) /14./, (Ho Chi Minh City, VN, 20221128) [2022] Download DOI: 10.1007/978-3-031-21967-2_35
  5. Vácha Pavel, Haindl MichalTextural Features Sensitivity to Scale and Illumination Variations , Advances in Computational Collective Intelligence : 14th International Conference, ICCCI 2022, p. 237-249 , Eds: Badica Costin, International Conference on Computational Collective Intelligence (ICCCI 2022) /14./, (Hammamet, TN, 20220926) [2022] Download DOI: 10.1007/978-3-031-16210-7_19
  6. Haindl Michal, Žid PavelMelanoma Recognition , Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, p. 722-729 , Eds: Farinella G.M., Radeva P., Bouatouch K., International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) /17./, (Setúbal - online, PT, 20220206) [2022] Download DOI: 10.5220/0000156800003124
  7. Havlíček Michal, Haindl MichalOptimized Texture Spectral Similarity Criteria , Advances in Computational Collective Intelligence, p. 644-655 , Eds: Wojtkiewicz Krystian, Treur Jan, Pimenidis Elias, Maleszka Marcin, International Conference on Computational Collective Intelligence 2021 /13./, (Kallithea, Rhodes, GR, 20210929) [2021] Download DOI: 10.1007/978-3-030-88113-9_52
  8. Moudrá A., Haindl MichalUnderground Archeological Structures Detection , Advances in Computational Collective Intelligence, p. 690-702 , Eds: Wojtkiewicz Krystian, Treur Jan, Pimenidis Elias, Maleszka Marcin, International Conference on Computational Collective Intelligence 2021 /13./, (Kallithea, Rhodes, GR, 20210929) [2021] Download DOI: 10.1007/978-3-030-88113-9_56
  9. Haindl Michal, Havlíček VojtěchTransfer Learning of Mixture Texture Models , Computational Collective Intelligence, p. 825-837 , Eds: Nguyen N. T., Hoang B. H., Huynh C. P., Hwang D., Trawinski B., Vossen G., International Conference on Computational Collective Intelligence 2020 /12./, (Da Nang, VN, 20201130) [2020] Download DOI: 10.1007/978-3-030-63007-2_65
  10. Haindl Michal, Havlíček Vojtěch3D Multi-frequency Fully Correlated Causal Random Field Texture Model , Pattern Recognition, p. 423-434 , Eds: Palaiahnakote Shivakumara, Sanniti di Baja Gabriella, Wang Liang, Yan Wei Qi, The 5th Asian Conference on Pattern Recognition (ACPR 2019), (Auckland, NZ, 20191126) [2020] Download DOI: 10.1007/978-3-030-41299-9_33
  11. Haindl Michal, Žid PavelConiferous Trees Needles-Based Taxonomy Classification , International Conference on Image and Vision Computing New Zealand 2019 (IVCNZ 2019), p. 1-6, Image and Vision Computing New Zealand (IVCNZ 2019) /34./, (Dunedin, NZ, 20191202) [2019] Download DOI: 10.1109/IVCNZ48456.2019.8961023
  12. Mikeš Stanislav, Haindl MichalView Dependent Surface Material Recognition , Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019), p. 156-167 , Eds: Bebis G., Boyle R., Parvin B., Koracin D., International Symposium on Visual Computing (ISVC 2019) /14./, (Lake Tahoe, US, 20191007) [2019] Download DOI: 10.1007/978-3-030-33720-9_12
  13. Haindl Michal, Havlíček MichalMutual Information-Based Texture Spectral Similarity Criterion , Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019), p. 302-314 , Eds: Bebis G., Boyle R., Parvin B., Koracin D., International Symposium on Visual Computing (ISVC 2019) /14./, (Lake Tahoe, US, 20191007) [2019] Download DOI: 10.1007/978-3-030-33720-9_23