Search results
- 1.0564063 - ÚFP 2023 RIV GB eng J - Journal Article
Zorek, M. - Škvára, V. - Smidl, L. - Pevný, T. - Seidl, Jakub - Grover, Ondřej
Semi-supervised deep networks for plasma state identification.
Plasma Physics and Controlled Fusion. Roč. 64, č. 12 (2022), č. článku 125004. ISSN 0741-3335. E-ISSN 1361-6587
R&D Projects: GA MŠMT(CZ) LM2018117; GA ČR(CZ) GA19-15229S
Institutional support: RVO:61389021
Keywords : plasma * neural networks * semi-supervised learning * classification
OECD category: Fluids and plasma physics (including surface physics)
Impact factor: 2.2, year: 2022
Method of publishing: Limited access
https://iopscience.iop.org/article/10.1088/1361-6587/ac9926
Permanent Link: https://hdl.handle.net/11104/0341367 - 2.0512092 - ÚI 2020 RIV DE eng C - Conference Paper (international conference)
Tumpach, J. - Krčál, M. - Holeňa, Martin
Deep networks in online malware detection.
ITAT 2019: Information Technologies – Applications and Theory. Aachen: Technical University & CreateSpace Independent Publishing, 2019 - (Barančíková, P.; Holeňa, M.; Horváth, T.; Pleva, M.; Rosa, R.), s. 90-98. CEUR Workshop Proceeding, 2473. ISSN 1613-0073.
[ITAT 2019: Conference Information Technologies - Applications and Theory /19./. Donovaly (SK), 20.09.2019-24.09.2019]
R&D Projects: GA ČR(CZ) GA18-18080S
Grant - others:GA MŠk(CZ) LM2015042
Institutional support: RVO:67985807
Keywords : artificial neural networks * multilayer perceptrons * deep networks * semi-supervised learning * malware detection
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-2473/paper7.pdf
Permanent Link: http://hdl.handle.net/11104/0302298File Download Size Commentary Version Access 0512092-aoa.pdf 3 581.3 KB OpenAccess Publisher’s postprint open-access - 3.0509321 - ÚI 2020 RIV DE eng C - Conference Paper (international conference)
Šabata, T. - Páll, J. E. - Holeňa, Martin
Deep Bayesian Semi-Supervised Active Learning for Sequence Labelling.
IAL ECML PKDD 2019: Workshop & Tutorial on Interactive Adaptive Learning. Proceedings. Aachen: Technical University & CreateSpace Independent Publishing Platform, 2019 - (Kottke, D.; Lemaire, D.; Calma, A.; Krempl, G.; Holzinger, A.), s. 80-95. CEUR Workshop Proceedings, 2444. ISSN 1613-0073.
[ECML PKDD 2019: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Würzburg (DE), 16.09.2019-20.09.2019]
R&D Projects: GA ČR(CZ) GA18-18080S
Institutional support: RVO:67985807
Keywords : Active Learning * Semi-supervised Learning * Bayesian Inference * Deep Learning * Sequence Labelling
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-2444/ialatecml_paper6.pdf
Permanent Link: http://hdl.handle.net/11104/0300071File Download Size Commentary Version Access 0509321-a.pdf 4 753.1 KB Publisher’s postprint require - 4.0493293 - ÚI 2019 RIV IE eng C - Conference Paper (international conference)
Šabata, T. - Pulc, Petr - Holeňa, Martin
Semi-supervised and Active Learning in Video Scene Classification from Statistical Features.
ECML PKDD 2018: Workshop on Interactive Adaptive Learning. Proceedings. Dublin, 2018 - (Krempl, G.; Lemaire, V.; Kottke, D.; Calma, A.; Holzinger, A.; Polikar, R.; Sick, B.), s. 24-35
[ECML PKDD 2018: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Dublin (IE), 10.09.2018-14.09.2018]
R&D Projects: GA ČR(CZ) GA18-18080S
Institutional support: RVO:67985807
Keywords : video data * scene classification * semi-supervised learning * active learning * colour statistics * feedforward neural networks
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Permanent Link: http://hdl.handle.net/11104/0286680File Download Size Commentary Version Access a0493293.pdf 13 602.4 KB Sborník dostupný online. Publisher’s postprint open-access - 5.0478628 - ÚI 2018 RIV DE eng C - Conference Paper (international conference)
Šabata, T. - Borovička, T. - Holeňa, Martin
K-best Viterbi Semi-supervized Active Learning in Sequence Labelling.
Proceedings ITAT 2017: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2017 - (Hlaváčová, J.), s. 144-152. 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 : active learning * semi-supervised learning * sequence labelling * Viterbi algorithm
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-1885/144.pdf
Permanent Link: http://hdl.handle.net/11104/0274763File Download Size Commentary Version Access a0478628.pdf 3 411.8 KB Publisher’s postprint require