Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Garbe, Christoph S."'
This paper presents a technique for finding the surface normal of an object from a set of images obtained under different lighting positions. The method presented is based on the principles of Photometric Stereo (PS) combined with Optimum Experimenta
Externí odkaz:
http://arxiv.org/abs/2204.05218
We address the vessel segmentation problem by building upon the multiscale feature learning method of Kiros et al., which achieves the current top score in the VESSEL12 MICCAI challenge. Following their idea of feature learning instead of hand-crafte
Externí odkaz:
http://arxiv.org/abs/1901.01562
Reference Setup for Quantitative Comparison of Segmentation Techniques for Short Glass Fiber CT Data
Autor:
Konopczyński, Tomasz, Rathore, Jitendra, Kröger, Thorben, Zheng, Lei, Garbe, Christoph S., Carmignato, Simone, Hesser, Jürgen
Comparing different algorithms for segmenting glass fibers in industrial computed tomography (CT) scans is difficult due to the absence of a standard reference dataset. In this work, we introduce a set of annotated scans of short-fiber reinforced pol
Externí odkaz:
http://arxiv.org/abs/1901.01210
Autor:
Konopczyński, Tomasz, Rathore, Danish, Rathore, Jitendra, Kröger, Thorben, Zheng, Lei, Garbe, Christoph S., Carmignato, Simone, Hesser, Jürgen
We present the first attempt to perform short glass fiber semantic segmentation from X-ray computed tomography volumetric datasets at medium (3.9 {\mu}m isotropic) and low (8.3 {\mu}m isotropic) resolution using deep learning architectures. We perfor
Externí odkaz:
http://arxiv.org/abs/1901.01211
Publikováno v:
In Neurocomputing 17 September 2021 453:85-96
Dust storms in the earth's major desert regions significantly influence microphysical weather processes, the CO$_2$-cycle and the global climate in general. Recent increases in the spatio-temporal resolution of remote sensing instruments have created
Externí odkaz:
http://arxiv.org/abs/1308.0469
Publikováno v:
The Annals of Applied Statistics, 2015 Sep 01. 9(3), 1298-1327.
Externí odkaz:
http://www.jstor.org/stable/43826422
Reference Setup for Quantitative Comparison of Segmentation Techniques for Short Glass Fiber CT Data
Autor:
Konopczy��ski, Tomasz, Rathore, Jitendra, Kr��ger, Thorben, Zheng, Lei, Garbe, Christoph S., Carmignato, Simone, Hesser, J��rgen
Comparing different algorithms for segmenting glass fibers in industrial computed tomography (CT) scans is difficult due to the absence of a standard reference dataset. In this work, we introduce a set of annotated scans of short-fiber reinforced pol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d182366320183751b29f9aaf21528f9
http://arxiv.org/abs/1901.01210
http://arxiv.org/abs/1901.01210
Publikováno v:
Proceedings of SPIE; 7/26/2019, Vol. 11144, p1-4, 4p