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pro vyhledávání: '"P, Mosinska"'
Akademický článek
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Autor:
Truong, Prune, Apostolopoulos, Stefanos, Mosinska, Agata, Stucky, Samuel, Ciller, Carlos, De Zanet, Sandro
Publikováno v:
In the IEEE International Conference on Computer Vision (ICCV), 2019, pp. 10732-10741
We introduce a novel CNN-based feature point detector - GLAMpoints - learned in a semi-supervised manner. Our detector extracts repeatable, stable interest points with a dense coverage, specifically designed to maximize the correct matching in a spec
Externí odkaz:
http://arxiv.org/abs/1908.06812
Detection of curvilinear structures in images has long been of interest. One of the most challenging aspects of this problem is inferring the graph representation of the curvilinear network. Most existing delineation approaches first perform binary s
Externí odkaz:
http://arxiv.org/abs/1905.03892
The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineati
Externí odkaz:
http://arxiv.org/abs/1811.10508
Delineation of curvilinear structures is an important problem in Computer Vision with multiple practical applications. With the advent of Deep Learning, many current approaches on automatic delineation have focused on finding more powerful deep archi
Externí odkaz:
http://arxiv.org/abs/1712.02190
Autor:
Yasmine Derradji, Agata Mosinska, Stefanos Apostolopoulos, Carlos Ciller, Sandro De Zanet, Irmela Mantel
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract Age-related macular degeneration (AMD) is a progressive retinal disease, causing vision loss. A more detailed characterization of its atrophic form became possible thanks to the introduction of Optical Coherence Tomography (OCT). However, ma
Externí odkaz:
https://doaj.org/article/99cc5b247c774ecc9830aa9e194367de
Publikováno v:
Proc. of Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017, pages 165-173
Many state-of-the-art delineation methods rely on supervised machine learning algorithms. As a result, they require manually annotated training data, which is tedious to obtain. Furthermore, even minor classification errors may significantly affect t
Externí odkaz:
http://arxiv.org/abs/1612.08036
Many recent delineation techniques owe much of their increased effectiveness to path classification algorithms that make it possible to distinguish promising paths from others. The downside of this development is that they require annotated training
Externí odkaz:
http://arxiv.org/abs/1512.00747
Autor:
Pawel Mierczynski, Magdalena Mosinska, Waldemar Maniukiewicz, Krasimir Vasilev, Malgorzata I. Szynkowska
Publikováno v:
Arabian Journal of Chemistry, Vol 13, Iss 1, Pp 3183-3195 (2020)
Monometallic copper, nickel and bimetallic Pd(Rh)-Cu(Ni) catalysts supported on a binary oxide containing various content of ZrO2 and Al2O3 were prepared by impregnation method. Their physicochemical and catalytic properties in oxy-steam reforming of
Externí odkaz:
https://doaj.org/article/55b367ca9b45445a9ee21589d7103d8b
Akademický článek
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