Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Bernhard X. Kausler"'
Publikováno v:
Computational Statistics. 34:945-976
We consider the problem of learning to detect anomalous time series from an unlabeled data set, possibly contaminated with anomalies in the training data. This scenario is important for applications in medicine, economics, or industrial quality contr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::121dee5796df211a825270165fe1e744
https://doi.org/10.1007/s00180-018-0824-9
https://doi.org/10.1007/s00180-018-0824-9
Autor:
Jan Lellmann, Jörg Hendrik Kappes, Carsten Rother, Bogdan Savchynskyy, Bernhard X. Kausler, Nikos Komodakis, Bjoern Andres, Christoph Schnörr, Thorben Kröger, Sungwoong Kim, Sebastian Nowozin, Fred A. Hamprecht, Dhruv Batra
Publikováno v:
International Journal of Computer Vision
International Journal of Computer Vision, Springer Verlag, 2015, ⟨10.1007/s11263-015-0809-x⟩
International Journal of Computer Vision, Springer Verlag, 2015, ⟨10.1007/s11263-015-0809-x⟩
International audience; Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov Random Fields (MRF). This study provided valuable insights in choosing the best optimization technique for certain classes of pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3e8fa0c9cd131122c1b8dab3b4d1809
https://hal.archives-ouvertes.fr/hal-01247122/document
https://hal.archives-ouvertes.fr/hal-01247122/document
Publikováno v:
2013 IEEE International Conference on Computer Vision.
The quality of any tracking-by-assignment hinges on the accuracy of the foregoing target detection / segmentation step. In many kinds of images, errors in this first stage are unavoidable. These errors then propagate to, and corrupt, the tracking res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0b6e9d5c1b7a43b5c7d21ede858c67d
https://doi.org/10.1109/iccv.2013.364
https://doi.org/10.1109/iccv.2013.364
Autor:
Nadine Peyriéras, Maria J. Ledesma-Carbayo, Wolfgang Driever, Bernhard X. Kausler, Karol Mikula, Periklis Pantazis, Pierre Geurts, Raphaël Marée, Rainer Stotzka, Thomas Dickmeis, Fred A. Hamprecht, Andres Santos, Olaf Ronneberger, Uwe Strähle, Ralf Mikut
Publikováno v:
Zebrafish, ISSN 1545-8547, 2013-08, Vol. 10, No. 3
Zebrafish
Zebrafish, Mary Ann Liebert, 2013, 10 (3), pp.401-421. ⟨10.1089/zeb.2013.0886⟩
Zebrafish, 2013, 10 (3), pp.401-421. ⟨10.1089/zeb.2013.0886⟩
Zebrafish, 10(3), 401-421. Mary Ann Liebert Inc (2013).
OpenAIRE
Open Repository and Bibliography-University of Liège
Archivo Digital UPM
Europe PubMed Central
instname
Zebrafish
Zebrafish, Mary Ann Liebert, 2013, 10 (3), pp.401-421. ⟨10.1089/zeb.2013.0886⟩
Zebrafish, 2013, 10 (3), pp.401-421. ⟨10.1089/zeb.2013.0886⟩
Zebrafish, 10(3), 401-421. Mary Ann Liebert Inc (2013).
OpenAIRE
Open Repository and Bibliography-University of Liège
Archivo Digital UPM
Europe PubMed Central
instname
International audience; Abstract Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed7ae602af19c45fa9f2a0d08e5a0634
http://oa.upm.es/26813/
http://oa.upm.es/26813/
Autor:
Dhruv Batra, Sungwoong Kim, Bjoern Andres, Jörg Hendrik Kappes, Fred A. Hamprecht, Sebastian Nowozin, Bernhard X. Kausler, Christoph Schnörr, Carsten Rother, Nikos Komodakis, Jan Lellmann
Publikováno v:
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition 2013
IEEE Conference on Computer Vision and Pattern Recognition 2013
IEEE Conference on Computer Vision and Pattern Recognition 2013, Jun 2013, Portland, United States. pp.1-8, ⟨10.1109/CVPR.2013.175⟩
CVPR
IEEE Conference on Computer Vision and Pattern Recognition 2013
IEEE Conference on Computer Vision and Pattern Recognition 2013, Jun 2013, Portland, United States. pp.1-8, ⟨10.1109/CVPR.2013.175⟩
CVPR
International audience; Even years ago, Szeliski et al. published an influential study on energy minimization methods for Markov random fields (MRF). This study provided valuable insights in choosing the best optimization technique for certain classe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a28a349a5c211801297fa2627ce61a60
https://hal-enpc.archives-ouvertes.fr/hal-00865699
https://hal-enpc.archives-ouvertes.fr/hal-00865699
Autor:
Lars Hufnagel, Jochen Wittbrodt, Martin Schiegg, Bjoern Andres, Heike Leitte, Martin Lindner, Bernhard X. Kausler, Ullrich Koethe, Fred A. Hamprecht
Publikováno v:
Computer Vision – ECCV 2012 ISBN: 9783642337116
ECCV (3)
ECCV (3)
Tracking by assignment is well suited for tracking a varying number of divisible cells, but suffers from false positive detections. We reformulate tracking by assignment as a chain graph---a mixed directed-undirected probabilistic graphical model---a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7f2cd457323948bacdc0534d1b866ea
https://doi.org/10.1007/978-3-642-33712-3_11
https://doi.org/10.1007/978-3-642-33712-3_11
Autor:
H. Janicke, Jochen Wittbrodt, Bernhard X. Kausler, Martin Lindner, Fred A. Hamprecht, B. Hockendorf, Ullrich Köthe, Frederik O. Kaster, Xinghua Lou
Publikováno v:
ISBI
We present DELTR, an automated pipeline for the analysis of time-resolved light sheet fluorescence microscopy images of zebrafish embryogenesis. It comprises 3D nucleus segmentation using shape-regularized graph cuts, parallelized extraction of geome
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f59768b52827531188251b1e9ba89a4a
https://doi.org/10.1109/isbi.2011.5872698
https://doi.org/10.1109/isbi.2011.5872698
Autor:
Buote Xu, Thorben Kroeger, Jaime I Cervantes, Ullrich Koethe, Martin Schiegg, Christoph N. Straehle, Markus Rudy, Dominik Kutra, Adrian Wolny, Janez Ales, Fynn Beuttenmueller, Anna Kreshuk, Kemal Eren, Carsten Haubold, Fred A. Hamprecht, Stuart Berg, Chong Zhang, Thorsten Beier, Bernhard X. Kausler
Publikováno v:
Nature Methods
We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise. It contains pre-defined workflows for image segmentation, object classification, coun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3547ce3310a015f5684ccf22c8b266e7
Autor:
MITTAL, AJAY1 ajaymittal@pu.ac.in, DHALLA, SABRINA1 sabrinadhala@gmail.com, GUPTA, SAVITA1 savitag@yahoo.com, GUPTA, AASTHA2 aasthagupta3@gmail.com
Publikováno v:
ACM Computing Surveys. 2022 Suppl 11, Vol. 54, p1-37. 37p.
Autor:
Kappes, Jörg1 kappes@math.uni-heidelberg.de, Andres, Bjoern2, Hamprecht, Fred1, Schnörr, Christoph1, Nowozin, Sebastian3, Batra, Dhruv4, Kim, Sungwoong5, Kausler, Bernhard1, Kröger, Thorben1, Lellmann, Jan6, Komodakis, Nikos7, Savchynskyy, Bogdan8, Rother, Carsten8
Publikováno v:
International Journal of Computer Vision. Nov2015, Vol. 115 Issue 2, p155-184. 30p. 5 Color Photographs, 4 Black and White Photographs, 3 Diagrams, 23 Charts.