Search results

  1. 1.
    0584178 - ÚFP 2024 RIV SK eng C - Conference Paper (international conference)
    Abbasi, S. - Mlynář, J. - Chlum, J. - Svoboda, V. - Svoboda, Jakub - Ficker, Ondřej - Brotánková, J.
    Machine-learning-based reconstruction of spatial distribution of plasma radiation using color visible cameras at golem tokamak.
    21st Conference of Czech and Slovak Physicists. Košice: Slovak Physical Society, 2023, (2023), s. 59-60. ISBN 9788089855216.
    [21st Conference of Czech and Slovak Physicists. Bratislava (SK), 04.09.2023-07.09.2023]
    Institutional support: RVO:61389021
    Keywords : tokamak * GOLEM * machine learning
    OECD category: Fluids and plasma physics (including surface physics)
    Permanent Link: https://hdl.handle.net/11104/0352161
     
     
  2. 2.
    0583897 - GFÚ 2024 RIV NL eng J - Journal Article
    Liu, H. - Harris, J. - Sherlock, R. - Behnia, P. - Grunsky, E. - Naghizadeh, M. - Rubingh, K. - Tuba, G. - Roots, E. A. - Hill, Graham J.
    Mineral prospectivity mapping using machine learning techniques for gold exploration in the Larder Lake area, Ontario, Canada.
    Journal of Geochemical Exploration. Roč. 253, October (2023), č. článku 107279. ISSN 0375-6742. E-ISSN 1879-1689
    Institutional support: RVO:67985530
    Keywords : mineral prospectivity mapping (MPM) * machine learning * partial least-squares-discriminant analysis (PLS-DA) * Random Forest (RF) * Larder Lake area
    OECD category: Geology
    Impact factor: 3.9, year: 2022
    Method of publishing: Limited access
    https://www.sciencedirect.com/science/article/abs/pii/S0375674223001267
    Permanent Link: https://hdl.handle.net/11104/0351880
    FileDownloadSizeCommentaryVersionAccess
    Liu2023JGeochemExploration.pdf119.4 MBPublisher’s postprintrequire
     
     
  3. 3.
    0582334 - ÚJF 2024 CZ eng D - Thesis
    Mrázková, Jitka
    Identification of c-jets in p+p and A+A collisions with machine learning.
    Ústav jaderné fyziky AV ČR, v. v. i. Defended: Fakulta jaderná a fyzikálně inženýrská ČVUT v Praze. 05.06.2023. - Praha: České vysoké učení technické v Praze, 2023. 60 s.
    Institutional support: RVO:61389005
    Keywords : jet physics * charm quarks * quark-gluon plasma * machine learning
    OECD category: Particles and field physics
    http://hdl.handle.net/10467/108558
    Permanent Link: https://hdl.handle.net/11104/0350445
     
     
  4. 4.
    0581659 - ÚTIA 2025 RIV NL eng J - Journal Article
    Baruník, Jozef - Hanus, Luboš
    Fan charts in era of big data and learning.
    Finance Research Letters. Roč. 61, č. 1 (2024), č. článku 105003. ISSN 1544-6123. E-ISSN 1544-6131
    R&D Projects: GA ČR(CZ) GX19-28231X
    Institutional support: RVO:67985556
    Keywords : Fan charts * Probabilistic forecasting * Machine learning
    OECD category: Applied Economics, Econometrics
    Impact factor: 10.4, year: 2022
    Method of publishing: Limited access
    https://www.sciencedirect.com/science/article/pii/S1544612324000333?dgcid=author http://library.utia.cas.cz/separaty/2023/E/barunik-0581659.pdf
    Permanent Link: https://hdl.handle.net/11104/0349774
     
     
  5. 5.
    0579619 - ÚEM 2024 RIV US eng J - Journal Article
    Pardini, B. - Ferrero, G. - Tarallo, S. - Gallo, G. - Francavilla, A. - Licheri, N. - Trompetto, M. - Clerico, G. - Senore, P. - Vymetálková, Veronika - Vodičková, Ludmila - Liška, V. - Vyčítal, O. - Levý, O. - Macinga, P. - Hucl, T. - Budinská, E. - Vodička, Pavel - Cordero, F. - Naccarati, A.
    A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study.
    Gastroenterology. Roč. 165, č. 3 (2023), s. 582-599. ISSN 0016-5085. E-ISSN 1528-0012
    R&D Projects: GA ČR(CZ) GA17-16857S; GA ČR(CZ) GA22-05942S; GA MZd(CZ) NV18-03-00199; GA MŠMT LX22NPO5102
    Institutional support: RVO:68378041
    Keywords : Stool MicroRNAs * Noninvasive Diagnosis * Small RNA Sequencing * Colorectal Cancer * Precancerous Lesions * Machine Learning
    OECD category: Biochemistry and molecular biology
    Impact factor: 29.4, year: 2022
    Method of publishing: Open access
    https://www.sciencedirect.com/science/article/pii/S0016508523008119?via%3Dihub
    Permanent Link: https://hdl.handle.net/11104/0348441
    FileDownloadSizeCommentaryVersionAccess
    Pardini 2023.pdf147.9 MBPublisher’s postprintopen-access
     
     
  6. 6.
    0579589 - ÚI 2024 RIV CH eng C - Conference Paper (international conference)
    Neruda, Roman - Figueroa-Garcia, J.C.
    Feature Selection for Performance Estimation of Machine Learning Workflows.
    International Conference on Information Technology and Systems: ICITS 2023, Volume 1. Cham: Springer, 2023 - (Rocha, A.; Ferrás, C.; Ibarra, W.), s. 351-359. Lecture Notes in Networks and Systems, 691. ISBN 978-3-031-33257-9. ISSN 2367-3370.
    [ICITS 2023: International Conference on Information Technology and Systems /6./. Cusco (PE), 24.04.2023-26.04.2023]
    Institutional support: RVO:67985807
    Keywords : Auto-ML * Machine learning * Performance estimation
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    https://doi.org/10.1007/978-3-031-33258-6_33
    Permanent Link: https://hdl.handle.net/11104/0348401
     
     
  7. 7.
    0579554 - ÚTIA 2024 RIV NL eng J - Journal Article
    Žid, Pavel - Haindl, Michal - Havlíček, Vojtěch
    Governmental Anti-Covid Measures Effectiveness Detection.
    Procedia Computer Science. Roč. 225, č. 1 (2023), s. 2922-2931. ISSN 1877-0509.
    [International Conference on Knowledge-Based and Intelligent Information & Engineering Systems 2023 (KES 2023) /27./. Athens, 06.09.2023-08.09.2023]
    R&D Projects: GA ČR(CZ) GA19-12340S
    Institutional support: RVO:67985556
    Keywords : COVID-19 * Recursive forecasting model * Machine learning method * Prediction * Anti-pandemic measures
    OECD category: Automation and control systems
    Method of publishing: Open access
    http://library.utia.cas.cz/separaty/2023/RO/zid-0579554.pdf https://www.sciencedirect.com/science/article/pii/S1877050923014436?via%3Dihub
    Permanent Link: https://hdl.handle.net/11104/0348913
     
     
  8. 8.
    0577928 - MÚA 2024 RIV US eng C - Conference Paper (international conference)
    Lanz, V. - Hajič, Jan
    Text boundaries do not provide a better segmentation of Gregorian antiphons.
    DLfM ’23: Proceedings of the 10th International Conference on Digital Libraries for Musicology. New York: Association for Computing Machinery, 2023 - (Thomae, M.), s. 72-76. ISBN 979-8-4007-0833-6.
    [International Conference on Digital Libraries for Musicology /10./. Milan (IT), 10.11.2023]
    Grant - others:John Templeton Foundation(US) 61913
    Program: Cultural Evolution Society Transformation Fund
    Source of funding: N - Non-public resources
    Keywords : digital musicology * Gregorian chant * machine learning
    OECD category: Performing arts studies (Musicology, Theater science, Dramaturgy)
    https://doi.org/10.1145/3625135.3625143
    Permanent Link: https://hdl.handle.net/11104/0347008
     
     
  9. 9.
    0577144 - ÚI 2024 RIV CH eng J - Journal Article
    Štěpánek, Lubomír - Dlouhá, Jana - Martinková, Patrícia
    Item Difficulty Prediction Using Item Text Features: Comparison of Predictive Performance across Machine-Learning Algorithms.
    Mathematics. Roč. 11, č. 19 (2023), č. článku 4104. ISSN 2227-7390
    R&D Projects: GA ČR(CZ) GA21-03658S
    Institutional support: RVO:67985807
    Keywords : text-based item difficulty prediction * text features and item wording * machine learning * regularization methods * elastic net regression * support vector machines * regression and decision trees * random forests * neural networks * algorithm vs. domain expert’s prediction performance
    Impact factor: 2.4, year: 2022
    Method of publishing: Open access
    https://dx.doi.org/10.3390/math11194104
    Permanent Link: https://hdl.handle.net/11104/0346365
    FileDownloadSizeCommentaryVersionAccess
    0577144-aoa.pdf0715.6 KBOA CC BY 4.0Publisher’s postprintopen-access
     
     
  10. 10.
    0576325 - PSÚ 2024 RIV CH eng C - Conference Paper (international conference)
    Mekyska, J. - Galáž, Z. - Šafárová, Katarína - Zvončák, V. - Čunek, Lukáš - Urbánek, Tomáš - Havigerová, Jana Marie - Bednářová, Jiřina - Mucha, J. - Gavenčiak, M. - Smékal, Z. - Faundez-Zanuy, M.
    Assessment of Developmental Dysgraphia Utilising a Display Tablet.
    Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition. Vol. 14285. Cham: Springer, 2023 - (Parziale, A.; Diaz, M.; Melo, F.), s. 21-35. ISBN 978-3-031-45460-8.
    [International Conference of the International Graphonomics Society /21./. Évora (PT), 16.10.2023-19.10.2023]
    R&D Projects: GA TA ČR(CZ) TL03000287
    Institutional support: RVO:68081740
    Keywords : developmental dysgraphia * handwriting difficulties * handwriting proficiency * online handwriting * computerised assessment * machine learning * display tablet
    OECD category: Psychology (including human - machine relations)
    https://link.springer.com/book/10.1007/978-3-031-45461-5
    Permanent Link: https://hdl.handle.net/11104/0345914
    FileDownloadSizeCommentaryVersionAccess
    0576325 M Šafárová et al_Assessment...pdf0805.8 KBAuthor´s preprintrequire
     
     

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