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pro vyhledávání: '"Ogier du Terrail, Jean"'
Autor:
Ogier du Terrail, Jean
Cette thèse présente une tentative d'approche du problème de la détection et discrimination des petits véhicules dans des images aériennes en vue verticale par l'utilisation de techniques issues de l'apprentissage profond ou "deep-learning". Le
Externí odkaz:
http://www.theses.fr/2018NORMC276/document
Autor:
Ogier du Terrail, Jean, Leopold, Armand, Joly, Clément, Béguier, Constance, Andreux, Mathieu, Maussion, Charles, Schmauch, Benoît, Tramel, Eric W., Bendjebbar, Etienne, Zaslavskiy, Mikhail, Wainrib, Gilles, Milder, Maud, Gervasoni, Julie, Guerin, Julien, Durand, Thierry, Livartowski, Alain, Moutet, Kelvin, Gautier, Clément, Djafar, Inal, Moisson, Anne-Laure, Marini, Camille, Galtier, Mathieu, Balazard, Félix, Dubois, Rémy, Moreira, Jeverson, Simon, Antoine, Drubay, Damien, Lacroix-Triki, Magali, Franchet, Camille, Bataillon, Guillaume, Heudel, Pierre-Etienne
Publikováno v:
Nature Medicine; January 2023, Vol. 29 Issue: 1 p135-146, 12p
Object detection-the computer vision task dealing with detecting instances of objects of a certain class (e.g., 'car', 'plane', etc.) in images-attracted a lot of attention from the community during the last 5 years. This strong interest can be expla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc46a708bab1c5ce875e3422849c73a8
Autor:
Ogier Du Terrail, Jean
The following manuscript is an attempt to tackle the problem of small vehicles detection in vertical aerial imagery through the use of deep learning algorithms. The specificities of the matter allows the use of innovative techniques leveraging the in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______166::c843403fc7ee016ba3e7e61eea043a44
https://theses.hal.science/tel-02113872
https://theses.hal.science/tel-02113872
Autor:
Ogier Du Terrail, Jean
CERN summer student report on a project including work on GEMs scintillators and PMTs.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________65::321e730cd5e0cb8a0534023ff643f21a
http://cds.cern.ch/record/1752567
http://cds.cern.ch/record/1752567