Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Tirtha Chanda"'
Autor:
Tirtha Chanda, Katja Hauser, Sarah Hobelsberger, Tabea-Clara Bucher, Carina Nogueira Garcia, Christoph Wies, Harald Kittler, Philipp Tschandl, Cristian Navarrete-Dechent, Sebastian Podlipnik, Emmanouil Chousakos, Iva Crnaric, Jovana Majstorovic, Linda Alhajwan, Tanya Foreman, Sandra Peternel, Sergei Sarap, İrem Özdemir, Raymond L. Barnhill, Mar Llamas-Velasco, Gabriela Poch, Sören Korsing, Wiebke Sondermann, Frank Friedrich Gellrich, Markus V. Heppt, Michael Erdmann, Sebastian Haferkamp, Konstantin Drexler, Matthias Goebeler, Bastian Schilling, Jochen S. Utikal, Kamran Ghoreschi, Stefan Fröhling, Eva Krieghoff-Henning, Reader Study Consortium, Titus J. Brinker
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet oft
Externí odkaz:
https://doaj.org/article/a7c398cf0b3b4b35ad5fc17b7f22b907
Publikováno v:
ECML PKDD 2020 Workshops ISBN: 9783030659646
PKDD/ECML Workshops
PKDD/ECML Workshops
In supervised machine learning solutions, obtaining labels for data is either expensive or labels are very difficult to come by. This has resulted in reliance on crowdworking for label acquisition. However, these labels come with a penalty of unrelia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23892107219b0810b713db25042cb712
https://doi.org/10.1007/978-3-030-65965-3_24
https://doi.org/10.1007/978-3-030-65965-3_24