Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Roland S. Zimmermann"'
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 6 (2021)
The mechanical contraction of the pumping heart is driven by electrical excitation waves running across the heart muscle due to the excitable electrophysiology of heart cells. With cardiac arrhythmias these waves turn into stable or chaotic spiral wa
Externí odkaz:
https://doaj.org/article/5dc0a11dc2524c988b826b0ad85109d7
Autor:
Ulrich Parlitz, Roland S. Zimmermann
Publikováno v:
Chaos (Woodbury, N.Y.). 28(4)
We present a dynamical observer for two dimensional partial differential equation models describing excitable media, where the required cross prediction from observed time series to not measured state variables is provided by Echo State Networks rece
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6ab285dca443bf371465296382b7cd5
https://pubmed.ncbi.nlm.nih.gov/31906670
https://pubmed.ncbi.nlm.nih.gov/31906670
Autor:
Wieland Brendel, Evgenia Rusak, Lukas Schott, Oliver Bringmann, Julian Bitterwolf, Roland S. Zimmermann, Matthias Bethge
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585792
ECCV (3)
ECCV (3)
The human visual system is remarkably robust against a wide range of naturally occurring variations and corruptions like rain or snow. In contrast, the performance of modern image recognition models strongly degrades when evaluated on previously unse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57c39738806dc3c1dc1d321cf0e12de5
https://doi.org/10.1007/978-3-030-58580-8_4
https://doi.org/10.1007/978-3-030-58580-8_4
Publikováno v:
Journal of Open Source Software. 5:2607
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d7c4d5da5e2441bd1df1abd56f13760
https://doi.org/10.21105/joss.02607
https://doi.org/10.21105/joss.02607
Publikováno v:
Computer Vision and Image Understanding. 188:102795
We present an auxiliary task to Mask R-CNN, an instance segmentation network, which leads to faster training of the mask head. Our addition to Mask R-CNN is a new prediction head, the Edge Agreement Head, which is inspired by the way human annotators
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bc8bae406436014ad1661adae64eb7f
https://doi.org/10.1016/j.cviu.2019.102795
https://doi.org/10.1016/j.cviu.2019.102795