Jan 20, 2020   7:02 a.m. Dalibor
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Persons at STU


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doc. Ing. Vanda Benešová, PhD.
Identification number: 63121
University e-mail: vanda_benesova [at] stuba.sk
 
Docentka CSc.,PhD. - Institute of Computer Engineering and Applied Informatics (FIIT)

Contacts     Lesson     Final thesis     Projects     Publications     Supervised theses     

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The selected person is an author of the following publications.

Ord.PublicationsType of resultYearDetails
1.Computational models of shape saliency
Polatsek, Patrik -- Jakab, Marek -- Benešová, Vanda -- Kužma, Matej
Computational models of shape saliency. In Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany. Bellingham: SPIE - Int Soc Optical Engineering, 2019, ISBN 9781510627482.
contributions in anthologies, chapters in monographs/textbooks, abstracts2019Details
2.Depth in the visual attention modelling from the egocentric perspective of view
Laco, Miroslav -- Benešová, Vanda
Depth in the visual attention modelling from the egocentric perspective of view. In Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany. Bellingham: SPIE - Int Soc Optical Engineering, 2019, ISBN 9781510627482.
contributions in anthologies, chapters in monographs/textbooks, abstracts2019Details
3.Hlboké neurónové siete a metódy počítačového videnia aplikované pre medicínske dáta
Baláž, Dávid -- Benešová, Vanda
Deep neural networks and methods of computer vision applied to medical data. Bachelor thesis. 2019.
final thesis2019Details
4.Modelovanie ľudskej vizuálnej pozornosti
Polatsek, Patrik -- Benešová, Vanda
Modelovanie ľudskej vizuálnej pozornosti. Dissertation thesis. 2019.
final thesis2019Details
5.Processing of acoustic signals by artificial intelligence methods
Hubar, Yurii -- Benešová, Vanda
Spracovanie akustických signálov metódami umelej inteligencie. Diploma thesis. 2019.
final thesis2019Details
6.Processing of visual medical data by computer vision methods and deep neural networks
Šefčík, František -- Benešová, Vanda
Spracovanie vizuálnych medicínskych dát metódami počítačového videnia a hlbokých neurónových sietí. Bachelor thesis. 2019.
final thesis2019Details
7.Recognition of advertising sequences in TV signal
Ďurica, Ján -- Benešová, Vanda
Rozpoznávanie reklamných sekvencií v televíznom signále. Diploma thesis. 2019.
final thesis2019Details
8.Segmentácia orgánov z trojrozmerných medicínskych dát metódami počítačového videnia
Kováčik, Michal -- Benešová, Vanda
Segmentácia orgánov z trojrozmerných medicínskych dát metódami počítačového videnia. Diploma thesis. 2019.
final thesis2019Details
9.Segmentation of gliomas in magnetic resonance images using recurrent neural networks.
Grivalský, Štefan -- Tamajka, Martin -- Benešová, Vanda
Segmentation of gliomas in magnetic resonance images using recurrent neural networks. In TSP 2019. Danvers: IEEE, 2019, p. 539--542. ISBN 978-1-7281-1864-2.
contributions in anthologies, chapters in monographs/textbooks, abstracts2019Details
10.Spracovanie volumetrických medicínskych dát metódami umelej inteligencie pre podporu lekárskej diagnostiky
Selecký, Ondrej -- Benešová, Vanda
Spracovanie volumetrických medicínskych dát metódami umelej inteligencie pre podporu lekárskej diagnostiky. Diploma thesis. 2019.
final thesis2019Details
11.The modeling of human visual attention using computer vision and artificial intelligence
Beka, Patrik -- Benešová, Vanda
Modelovanie ľudskej vizuálnej pozornosti metódami počítačového videnia a umelej inteligencie. Diploma thesis. 2019.
final thesis2019Details
12.Transforming Convolutional Neural Network to an Interpretable Classifier
Tamajka, Martin -- Benešová, Vanda -- Kompánek, Matej
Transforming Convolutional Neural Network to an Interpretable Classifier. In Proceedings IWSSIP 2019. [S. l.]: IEEE, 2019, p. 255--259. ISBN 978-1-7281-3227-3.
contributions in anthologies, chapters in monographs/textbooks, abstracts2019Details
13.Unsupervised similarity learning from compressed representations via Siamese autoencoders
Jakab, Marek -- Benešová, Vanda
Unsupervised similarity learning from compressed representations via Siamese autoencoders. In Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany. Bellingham: SPIE - Int Soc Optical Engineering, 2019, p. 110412. ISBN 9781510627482.
contributions in anthologies, chapters in monographs/textbooks, abstracts2019Details
14.Volumetrie Data Augmentation as an Effective Tool in MRI Classification Using 3D Convolutional Neural Network
Kompánek, Matej -- Tamajka, Martin -- Benešová, Vanda
Volumetrie Data Augmentation as an Effective Tool in MRI Classification Using 3D Convolutional Neural Network. In Proceedings IWSSIP 2019. [S. l.]: IEEE, 2019, p. 115--119. ISBN 978-1-7281-3227-3.
contributions in anthologies, chapters in monographs/textbooks, abstracts2019Details

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