Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Apprentissage multi-tâche"'
Autor:
Boutillon, Arnaud
Publikováno v:
Image Processing [eess.IV]. Ecole nationale supérieure Mines-Télécom Atlantique, 2022. English. ⟨NNT : 2022IMTA0311⟩
In medical imaging, segmentation using deep learning enables an automatic generation of anatomical models that are crucial for morphological evaluation. However, the scarcity of pediatric imaging resources may result in reduced accuracy and generaliz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1398::36c62de4568a105b6e73462416683b82
https://theses.hal.science/tel-03906771
https://theses.hal.science/tel-03906771
Autor:
Boutillon, Arnaud
In medical imaging, segmentation using deep learning enables an automatic generation of anatomical models that are crucial for morphological evaluation. However, the scarcity of pediatric imaging resources may result in reduced accuracy and generaliz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______166::36c62de4568a105b6e73462416683b82
https://theses.hal.science/tel-03906771
https://theses.hal.science/tel-03906771
Autor:
Pham, Minh-Quang
Publikováno v:
Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2021. English. ⟨NNT : 2021UPASG109⟩
Today, neural machine translation (NMT) systems constitute state-of-the-art systems in machine translation. However, such translation models require relatively large train data and struggle to handle a specific domain text. A domain may consist of te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______165::2750735ef72bb041cd3032bf1447f8cd
https://theses.hal.science/tel-03546910
https://theses.hal.science/tel-03546910
Autor:
Antelmi, Luigi
Publikováno v:
Statistics [math.ST]. INRIA Sophia Antipolis-Méditerranée; Université Côte d'Azur, 2021. English
Statistics [math.ST]. Université Côte d'Azur, 2021. English. ⟨NNT : 2021COAZ4050⟩
Statistics [math.ST]. Université Côte d'Azur, 2021. English. ⟨NNT : 2021COAZ4050⟩
This thesis presents new computational tools for the joint modeling of multi-modal biomedical data,robust to missing data, with application to neuroimaging studies in dementia. The theoretical base for this work is the Variational Autoencoder (VAE),
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b11e7bf4604639e4569934c0cae40132
https://hal.archives-ouvertes.fr/tel-03289782/file/main.pdf
https://hal.archives-ouvertes.fr/tel-03289782/file/main.pdf
Autor:
Bernard, Timothée
Publikováno v:
Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale
Traitement Automatique des Langues Naturelles
Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.268-269
Traitement Automatique des Langues Naturelles
Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.268-269
International audience; Nous présentons des résumés en français et en anglais de l’article (Bernard, 2021), présenté lors de la conférence 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::703b53606d8659a6c58a1b56d27e6bda
https://hal.archives-ouvertes.fr/hal-03265885/file/227.pdf
https://hal.archives-ouvertes.fr/hal-03265885/file/227.pdf
Autor:
Dockes, Jérôme
Publikováno v:
Machine Learning [stat.ML]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLT048⟩
Thousands of neuroimaging studies are published every year. Exploiting this huge amount of results is difficult. Indeed, individual studies lack statistical power and report many spurious findings. Even genuine effects are often specific to particula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2592::3fbab2623daf2159239eeb4ae76f262c
https://pastel.archives-ouvertes.fr/tel-02495783
https://pastel.archives-ouvertes.fr/tel-02495783
Autor:
Dockes, Jérôme
Publikováno v:
Machine Learning [stat.ML]. Télécom ParisTech, 2019. English
Machine Learning [stat.ML]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLT048⟩
Machine Learning [stat.ML]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLT048⟩
Thousands of neuroimaging studies are published every year. Exploiting this huge amount of results is difficult. Indeed, individual studies lack statistical power and report many spurious findings. Even genuine effects are often specific to particula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3fbab2623daf2159239eeb4ae76f262c
https://hal.archives-ouvertes.fr/tel-02469097/document
https://hal.archives-ouvertes.fr/tel-02469097/document
Autor:
Mordan, Taylor
Publikováno v:
Computer Vision and Pattern Recognition [cs.CV]. Sorbonne Université, 2018. English. ⟨NNT : 2018SORUS270⟩
Computer Vision and Pattern Recognition [cs.CV]. EDITE, 2018. English
Computer Vision and Pattern Recognition [cs.CV]. EDITE, 2018. English
Nowadays, images are ubiquitous through the use of smartphones and social media. It then becomes necessary to have automatic means of processing them, in order to analyze and interpret the large amount of available data. In this thesis, we are intere
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::06bc3020d2f69cfe77e135fc8045d2b6
https://tel.archives-ouvertes.fr/tel-02868569/document
https://tel.archives-ouvertes.fr/tel-02868569/document
Autor:
Zhang, Ruocong
Publikováno v:
Apprentissage [cs.LG]. Télécom ParisTech, 2014. Français. ⟨NNT : 2014ENST0049⟩
The goal of this work is to predict the returns of financial assets with statistical learning methods. We are motivated by the problem of stock selection in portfolio management. In particular, we will focus on the prediction of the sign of future re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______212::3dde4e8f94ecc5725e74695019f224c7
https://tel.archives-ouvertes.fr/tel-01856339
https://tel.archives-ouvertes.fr/tel-01856339