Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Palo, Kaupo"'
Inverse problems in image reconstruction are fundamentally complicated by unknown noise properties. Classical iterative deconvolution approaches amplify noise and require careful parameter selection for an optimal trade-off between sharpness and grai
Externí odkaz:
http://arxiv.org/abs/2308.09426
Metainformation is a common companion to biomedical images. However, this potentially powerful additional source of signal from image acquisition has had limited use in deep learning methods, for semantic segmentation in particular. Here, we incorpor
Externí odkaz:
http://arxiv.org/abs/2308.09411
Autor:
Papkov, Mikhail, Roberts, Kenny, Madissoon, Lee Ann, Bayraktar, Omer, Fishman, Dmytro, Palo, Kaupo, Parts, Leopold
Biomedical images are noisy. The imaging equipment itself has physical limitations, and the consequent experimental trade-offs between signal-to-noise ratio, acquisition speed, and imaging depth exacerbate the problem. Denoising is, therefore, an ess
Externí odkaz:
http://arxiv.org/abs/2011.05105
Autor:
Ali, Mohammed A.S., Misko, Oleg, Salumaa, Sten-Oliver, Papkov, Mikhail, Palo, Kaupo, Fishman, Dmytro *, Parts, Leopold **
Publikováno v:
In SLAS Discovery October 2021 26(9):1125-1137
In gauge theories with an extended Higgs sector the classical equations of motion can have solutions that describe stable, closed finite energy vortices. Such vortices separate two disjoint Higgs vacua, with one of the vacua embedded in the other in
Externí odkaz:
http://arxiv.org/abs/hep-th/9807228
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 1999 Nov . 96(24), 13756-13761.
Externí odkaz:
https://www.jstor.org/stable/121294
Autor:
Palo, Kaupo
Publikováno v:
Phys.Lett. B321 (1994) 61-65
Recently it has been argued, that Poincar\'{e} supersymmetric field theories admit an underlying loop space hamiltonian (symplectic) structure. Here shall establish this at the level of a general $N=1$ supermultiplet. In particular, we advocate the u
Externí odkaz:
http://arxiv.org/abs/hep-th/9311110
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Ali, Mohammed A. S., Misko, Oleg, Salumaa, Sten-Oliver, Papkov, Mikhail, Palo, Kaupo, Fishman, Dmytro, Parts, Leopold
Supplemental material, sj-pdf-1-jbx-10.1177_24725552211023214 for Evaluating Very Deep Convolutional Neural Networks for Nucleus Segmentation from Brightfield Cell Microscopy Images by Mohammed A. S. Ali, Oleg Misko, Sten-Oliver Salumaa, Mikhail Papk
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14001c42a745ba0c1e703cc7ab0444eb
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.