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pro vyhledávání: '"Jonathan Cheung-Wai Chana"'
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging
Autor:
Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia, Ine Dirks, Mitchel Alioscha-Perez, Nikos Deligiannis, Panagiotis Gonidakis, Sebastian Amador, REDONA BRAHIMETAJ, Evgenia Papavasileiou, Jonathan Cheung-Wai Chana, Fei Li, Shangzhen Song, Yixin Yang, Sofie Tilborghs, Siri Willems, Tom Eelbode, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Paul Suetens, Lucas Fidon, Tom Vercauteren, David Robben, Arne Brys, Dirk Smeets, Bart Ilsen, Nico Buls, Nina Watté, Johan de Mey, Annemiek Snoeckx, Parizel, Paul M., Julien Guiot, Louis Deprez, Paul Meunier, Stefaan Gryspeerdt, Kristof De Smet, Bart Jansen, Jef Vandemeulebroucke
Publikováno v:
Vrije Universiteit Brussel
University of Western Australia
University of Western Australia
Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised classification pipeline that employs variational autoencoders to extrac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da305250b2e4ddcc03553dd6b4b1dfff
https://researchportal.vub.be/en/publications/c6273017-9038-4fac-83de-80c1027c54f7
https://researchportal.vub.be/en/publications/c6273017-9038-4fac-83de-80c1027c54f7
