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of 3
pro vyhledávání: '"James Batten"'
Autor:
David Zimmerer, Peter M. Full, Fabian Isensee, Paul Jager, Tim Adler, Jens Petersen, Gregor Kohler, Tobias Ross, Annika Reinke, Antanas Kascenas, Bjorn Sand Jensen, Alison Q. O'Neil, Jeremy Tan, Benjamin Hou, James Batten, Huaqi Qiu, Bernhard Kainz, Nina Shvetsova, Irina Fedulova, Dmitry V. Dylov, Baolun Yu, Jianyang Zhai, Jingtao Hu, Runxuan Si, Sihang Zhou, Siqi Wang, Xinyang Li, Xuerun Chen, Yang Zhao, Sergio Naval Marimont, Giacomo Tarroni, Victor Saase, Lena Maier-Hein, Klaus Maier-Hein
Detecting Out-of-Distribution (OoD) data is one of the greatest challenges in safe and robust deployment of machine learning algorithms in medicine. When the algorithms encounter cases that deviate from the distribution of the training data, they oft
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4bd09f323a99e76832914cf9e01598d2
http://hdl.handle.net/10044/1/96881
http://hdl.handle.net/10044/1/96881
Publikováno v:
Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis
Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis ISBN: 9783030972806
Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis ISBN: 9783030972806
Using self-supervision in anomaly detection can increase sensitivity to subtle irregularities. However, increasing sensitivity to certain classes of outliers could result in decreased sensitivity to other types. While a single model may have limited
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::074db8b1fcecaf0cba313ab04b85a666
http://hdl.handle.net/10044/1/96833
http://hdl.handle.net/10044/1/96833
Autor:
James Batten
Publikováno v:
Educational and Psychological Measurement. 33:511-512
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efcb62161c6422a3fd9a4fa97a524887
https://doi.org/10.1177/001316447303300242
https://doi.org/10.1177/001316447303300242
