Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Eduardo Hugo Sanchez"'
Autor:
Damien Pouessel, Soléakhéna Ken, Valérie Gouaze-Andersson, Lucie Piram, Augustin Mervoyer, Delphine Larrieu-Ciron, Bastien Cabarrou, Amélie Lusque, Marie Robert, Jean-Sebastien Frenel, Emmanuelle Uro-Coste, Pascale Olivier, Muriel Mounier, Umberto Sabatini, Eduardo Hugo Sanchez, Mehdi Zouitine, Ahmad Berjaoui, Elizabeth Cohen-Jonathan Moyal
Publikováno v:
The Oncologist.
Background Hypofractionated stereotactic radiotherapy (hFSRT) is a salvage option for recurrent glioblastoma (GB) which may synergize anti-PDL1 treatment. This phase I study evaluated the safety and the recommended phase II dose of anti-PDL1 durvalum
Publikováno v:
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track ISBN: 9783030676667
ECML/PKDD (4)
ECML/PKDD (4)
Recently several models have been developed to reduce the annotation effort which is required to perform semantic segmentation. Instead of learning from pixel-level annotations, these models learn from cheaper annotations, e.g. image-level labels, sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59efc3acb34170bbcacc0778deface2c
https://doi.org/10.1007/978-3-030-67667-4_24
https://doi.org/10.1007/978-3-030-67667-4_24
Publikováno v:
ECCV 2020: Computer Vision
16th European Conference on Computer Vision-ECCV 2020
16th European Conference on Computer Vision-ECCV 2020, Aug 2020, online, France. pp.205-221, ⟨10.1007/978-3-030-58542-6_13⟩
Computer Vision – ECCV 2020 ISBN: 9783030585419
ECCV (22)
16th European Conference on Computer Vision-ECCV 2020
16th European Conference on Computer Vision-ECCV 2020, Aug 2020, online, France. pp.205-221, ⟨10.1007/978-3-030-58542-6_13⟩
Computer Vision – ECCV 2020 ISBN: 9783030585419
ECCV (22)
ISBN 978-3-030-58541-9; International audience; In this paper, we investigate the problem of learning disentangled representations. Given a pair of images sharing some attributes, we aim to create a low-dimensional representation which is split into
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21417f42188851d85ef9e1945396ac42
https://hal.archives-ouvertes.fr/hal-02397803/file/main.pdf
https://hal.archives-ouvertes.fr/hal-02397803/file/main.pdf
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030461324
ECML/PKDD (3)
ECML/PKDD (3)
In this paper, we investigate how to learn a suitable representation of satellite image time series in an unsupervised manner by leveraging large amounts of unlabeled data. Additionally, we aim to disentangle the representation of time series into tw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::879af9b70c034d2478d44f98d94a94d0
https://doi.org/10.1007/978-3-030-46133-1_19
https://doi.org/10.1007/978-3-030-46133-1_19