Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sebastian Wirkert"'
Autor:
Leonardo Ayala, Diana Mindroc-Filimon, Maike Rees, Marco Hübner, Jan Sellner, Silvia Seidlitz, Minu Tizabi, Sebastian Wirkert, Alexander Seitel, Lena Maier-Hein
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-9 (2024)
Abstract Spectral imaging has the potential to become a key technique in interventional medicine as it unveils much richer optical information compared to conventional RBG (red, green, and blue)-based imaging. Thus allowing for high-resolution functi
Externí odkaz:
https://doaj.org/article/3f1829251e2c4943801082e6ef6b7409
Lidar became an important component of the perception systems in autonomous driving. But challenges of training data acquisition and annotation made emphasized the role of the sensor to sensor domain adaptation. In this work, we address the problem o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f22a46f56381419f65e53b63bdb5a8f5
Autor:
Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi-Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle
Publikováno v:
Deep Neural Networks and Data for Automated Driving ISBN: 9783031012327
Fingscheidt, Gottschalk et al. (Hg.): Deep Neural Networks and Data for Automated Driving. Robustness, Uncertainty Quantification, and Insights Towards Safety
Fingscheidt, Gottschalk et al. (Hg.): Deep Neural Networks and Data for Automated Driving. Robustness, Uncertainty Quantification, and Insights Towards Safety
The use of deep neural networks (DNNs) in safety-critical applications like mobile health and autonomous driving is challenging due to numerous model-inherent shortcomings. These shortcomings are diverse and range from a lack of generalization over i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a97320425a5b7fac20b0272cdc9fe19b
https://doi.org/10.1007/978-3-031-01233-4_1
https://doi.org/10.1007/978-3-031-01233-4_1
Autor:
Leonardo Ayala, Tim J. Adler, Silvia Seidlitz, Sebastian Wirkert, Christina Engels, Alexander Seitel, Jan Sellner, Alexey Aksenov, Matthias Bodenbach, Pia Bader, Sebastian Baron, Anant Vemuri, Manuel Wiesenfarth, Nicholas Schreck, Diana Mindroc, Minu Tizabi, Sebastian Pirmann, Brittaney Everitt, Annette Kopp-Schneider, Dogu Teber, Lena Maier-Hein
Publikováno v:
medRxiv
Laparoscopic surgery has evolved as a key technique for cancer diagnosis and therapy. While characterization of the tissue perfusion is crucial in various procedures, such as partial nephrectomy, doing so by means of visual inspection remains highly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71da4e5a62db79b8ec7f183507f227ef
Publikováno v:
International Conference on Pattern Recognition (ICPR)
International Conference on Pattern Recognition (ICPR), Aug 2010, Istanbul, Turkey. pp.2077-2080, ⟨10.1109/ICPR.2010.511⟩
ICPR
International Conference on Pattern Recognition (ICPR), Aug 2010, Istanbul, Turkey. pp.2077-2080, ⟨10.1109/ICPR.2010.511⟩
ICPR
International audience; Occlusions are serious challenges when trackingmultiple targets. By greatly changing the measurement,they imply strong inter-target dependencies. Exactcomputation of these dependencies is not feasible. Theapproximations made b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5755916f8ee5a6b02d63a21594bca268
https://hal.archives-ouvertes.fr/hal-01381502
https://hal.archives-ouvertes.fr/hal-01381502