Search results
- 1.0573225 - FZÚ 2024 RIV US eng J - Journal Article
Chalupský, Jaromír - Vozda, Vojtěch - Hering, J. - Kybic, J. - Burian, Tomáš - Dziarzhytski, S. - Frantálová, Kateřina - Hájková, Věra - Jelínek, Šimon - Juha, Libor - Keitel, B. - Kuglerová, Zuzana - Kuhlmann, M. - Petryshak, B. - Ruiz-Lopez, M. - Vyšín, Luděk - Wodzinski, T. - Plönjes, E.
Deep learning for laser beam imprinting.
Optics Express. Roč. 31, č. 12 (2023), s. 19703-19721. ISSN 1094-4087
R&D Projects: GA ČR(CZ) GA20-08452S
EU Projects: European Commission(XE) 654148 - LASERLAB-EUROPE
Institutional support: RVO:68378271
Keywords : ablation imprinting methods * multi-layer convolutional neural network (U-Net) method employed for the first time
OECD category: Fluids and plasma physics (including surface physics)
Impact factor: 3.8, year: 2022
Method of publishing: Open access
Permanent Link: https://hdl.handle.net/11104/0343695File Download Size Commentary Version Access 0573225.pdf 0 16.8 MB Optica Open Access Publishing Agreement Publisher’s postprint open-access - 2.0571255 - ÚTIA 2024 RIV CH eng C - Conference Paper (international conference)
Lébl, Matěj - Šroubek, Filip - Flusser, Jan
Impact of Image Blur on Classification and Augmentation of Deep Convolutional Networks.
Image Analysis: 23rd Scandinavian Conference, SCIA 2023. Cham: Springer, 2023 - (Gade, R.), s. 108-117. Lecture notes on computer science, LNCS 13886. ISBN 978-3-031-31437-7.
[Scandinavian Conference on Image Analysis 2023 /23./. Levi (FI), 18.04.2023-21.04.2023]
R&D Projects: GA ČR GA21-03921S
Institutional support: RVO:67985556
Keywords : Image recognition * Blur * Augmentation of the training set * Convolutional neural network
OECD category: Computer hardware and architecture
http://library.utia.cas.cz/separaty/2023/ZOI/lebl-0571255.pdf
Permanent Link: https://hdl.handle.net/11104/0342934 - 3.0570880 - ÚPT 2024 RIV GB eng J - Journal Article
Shamaei, Amirmohammad - Starčuková, Jana - Starčuk jr., Zenon
Physics-informed deep learning approach to quantification of human brain metabolites from magnetic resonance spectroscopy data.
Computers in Biology Medicine. Roč. 158, May (2023), č. článku 106837. ISSN 0010-4825. E-ISSN 1879-0534
R&D Projects: GA MŠMT(CZ) EF18_046/0016045; GA MŠMT(CZ) LM2018129; GA MŠMT(CZ) LM2023050
EU Projects: European Commission(XE) 813120 - INSPiRE-MED
Institutional support: RVO:68081731
Keywords : MR spectroscopy * Inverse problem * Deep learning * Machine learning * Convolutional neural network * Metabolite quantification
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 7.7, year: 2022
Method of publishing: Open access
https://www.sciencedirect.com/science/article/pii/S0010482523003025
Permanent Link: https://hdl.handle.net/11104/0342210File Download Size Commentary Version Access 2023_Shamaei_ComputersInBiologyMedicine.pdf 4 8.6 MB OA - CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Publisher’s postprint open-access
Research data: Zenodo - 4.0547970 - BÚ 2022 RIV CH eng J - Journal Article
Korznikov, K. A. - Kislov, D. E. - Altman, Jan - Doležal, Jiří - Vozmishcheva, A. S. - Krestov, P. V.
Using the U-Net-like deep convolutional neural networks for precise tree recognition in very high resolution RGB (red, green, blue) satellite images.
Forests. Roč. 12, č. 1 (2021), č. článku 66. E-ISSN 1999-4907
Institutional support: RVO:67985939
Keywords : tree recognition * machine learning * convolutional neural network
OECD category: Ecology
Impact factor: 3.282, year: 2021
Method of publishing: Open access
Permanent Link: http://hdl.handle.net/11104/0324109File Download Size Commentary Version Access AltmanDolezal Forests.pdf 0 7.6 MB Publisher’s postprint open-access - 5.0546470 - ÚTIA 2022 RIV US eng C - Conference Paper (international conference)
Rozumnyi, D. - Matas, J. - Šroubek, Filip - Pollefeys, M. - Oswald, M.R.
FMODetect: Robust Detection of Fast Moving Objects.
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). Piscataway: IEEE, 2021, s. 3541-3549. ISBN 978-1-6654-2812-5. E-ISSN 2380-7504.
[International Conference on Computer Vision (ICCV) 2021. Piscataway (on-line) (US), 11.10.2021-17.10.2021]
R&D Projects: GA ČR GA21-03921S
Institutional support: RVO:67985556
Keywords : tracking * convolutional neural network * deconvolution
OECD category: Computer hardware and architecture
http://library.utia.cas.cz/separaty/2021/ZOI/sroubek-0546470.pdf
Permanent Link: http://hdl.handle.net/11104/0323758 - 6.0542182 - GFÚ 2022 RIV CZ eng J - Journal Article
Kolář, Petr - Petružálek, Matěj
Type analysis of laboratory seismic events by convolutional neural networks.
Acta geodynamica et geomaterialia. Roč. 18, č. 2 (2021), s. 267-277. ISSN 1214-9705. E-ISSN 2336-4351
R&D Projects: GA ČR(CZ) GA21-26542S
Institutional support: RVO:67985530 ; RVO:67985831
Keywords : convolutional neural network * machine learning * earthquake identification * acoustic emission * seismic signal processing * Bayesian optimization
OECD category: Volcanology; Volcanology (GLU-S)
Impact factor: 1.000, year: 2021
Method of publishing: Open access
https://www.irsm.cas.cz/index_en.php?page=acta_detail_doi&id=398
Permanent Link: http://hdl.handle.net/11104/0319659File Download Size Commentary Version Access Kolar2021AGG.pdf 1 3.6 MB Publisher’s postprint open-access - 7.0534541 - ÚTIA 2021 RIV GB eng C - Conference Paper (international conference)
Phan, A. H. - Sobolev, K. - Sozykin, K. - Ermilov, D. - Gusak, J. - Tichavský, Petr - Glukhov, V. - Oseledets, I. - Cichocki, A.
Stable Low-Rank Tensor Decomposition for Compression of Convolutional Neural Network.
ECCV 2020. Cham: Springer Nature Switzerland AG 2020, 2020 - (Vedaldi, A.; Bischof, H.; Brox, T.; Frahm, J.), s. 522-539. Lecture Notes in Computer Science, LNCS, 12374. ISBN 978-3-030-58525-9. ISSN 0302-9743. E-ISSN 1611-3349.
[European Conference on Computer Vision 2020 /16./. Glasgow (GB), 23.08.2020-28.08.2020]
Institutional support: RVO:67985556
Keywords : Convolutional neural network acceleration * Low-rank tensor decomposition * Degeneracy correction
OECD category: Electrical and electronic engineering
http://library.utia.cas.cz/separaty/2020/SI/tichavsky-0534541.pdf
Permanent Link: http://hdl.handle.net/11104/0313191 - 8.0510488 - ÚTIA 2020 RIV CH eng C - Conference Paper (international conference)
Mikeš, Stanislav - Haindl, Michal
View Dependent Surface Material Recognition.
Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019). Cham: Springer, 2019 - (Bebis, G.; Boyle, R.; Parvin, B.; Koracin, D.), s. 156-167, č. článku 12. Lecture Notes in Computer Science, 11844. ISBN 978-3-030-33719-3. ISSN 0302-9743. E-ISSN 1611-3349.
[International Symposium on Visual Computing (ISVC 2019) /14./. Lake Tahoe (US), 07.10.2019-09.10.2019]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : convolutional neural network * texture recognition * Bidirectional Texture Function recognition
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2019/RO/haindl-0510488.pdf
Permanent Link: http://hdl.handle.net/11104/0302678 - 9.0495384 - ÚPT 2019 RIV GB eng J - Journal Article
Plešinger, Filip - Nejedlý, Petr - Viščor, Ivo - Halámek, Josef - Jurák, Pavel
Parallel use of a convolutional neural network and bagged tree ensemble for the classification of Holter ECG.
Physiological Measurement. Roč. 39, č. 9 (2018), č. článku 094002. ISSN 0967-3334. E-ISSN 1361-6579
R&D Projects: GA ČR GA17-13830S; GA MŠMT(CZ) LO1212
Grant - others:AV ČR(CZ) MSM100651602
Program: Program na podporu mezinárodní spolupráce začínajících výzkumných pracovníků
Institutional support: RVO:68081731
Keywords : ECG * atrial fibrillation * arrhythmia * holter * automated processing * convolutional neural network * machine learning
OECD category: Medical laboratory technology (including laboratory samples analysis
Impact factor: 2.246, year: 2018
Permanent Link: http://hdl.handle.net/11104/0288373 - 10.0478627 - ÚI 2018 RIV DE eng C - Conference Paper (international conference)
Kopp, M. - Nikl, M. - Holeňa, Martin
Breaking CAPTCHAs with Convolutional Neural Networks.
Proceedings ITAT 2017: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2017 - (Hlaváčová, J.), s. 93-99. CEUR Workshop Proceedings, V-1885. ISBN 978-1974274741. ISSN 1613-0073.
[ITAT 2017. Conference on Theory and Practice of Information Technologies - Applications and Theory /17./. Martinské hole (SK), 22.09.2017-26.09.2017]
R&D Projects: GA ČR GA17-01251S
Grant - others:ČVUT(CZ) SGS17/210/OHK3/3T/18
Institutional support: RVO:67985807
Keywords : CAPTCHA * convolutional neural network * network security * optical character recognition
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-1885/93.pdf
Permanent Link: http://hdl.handle.net/11104/0274764File Download Size Commentary Version Access a0478627.pdf 1 2.8 MB Publisher’s postprint require