Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Sergio Naval Marimont"'
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
Autor:
Sergio Naval Marimont, Giacomo Tarroni
Publikováno v:
Medical Image Understanding and Analysis ISBN: 9783031120527
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bf074df24a919fdcf64ea397f7d3e72
https://doi.org/10.1007/978-3-031-12053-4_29
https://doi.org/10.1007/978-3-031-12053-4_29
Autor:
Sergio Naval Marimont, Giacomo Tarroni
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030871956
MICCAI (2)
MICCAI 2021
MICCAI (2)
MICCAI 2021
We propose a novel unsupervised out-of-distribution detection method for medical images based on implicit fields image representations. In our approach, an auto-decoder feed-forward neural network learns the distribution of healthy images in the form
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ae9719edd3e8395fbc2299f9f46154b
https://doi.org/10.1007/978-3-030-87196-3_18
https://doi.org/10.1007/978-3-030-87196-3_18
Autor:
Giacomo Tarroni, Sergio Naval Marimont
Publikováno v:
ISBI
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
We propose an out-of-distribution detection method that combines density and restoration-based approaches using Vector-Quantized Variational Auto-Encoders (VQ-VAEs). The VQ-VAE model learns to encode images in a categorical latent space. The prior di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6d069b1346c0d617cf57d52983f69ca