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pro vyhledávání: '"Pibre, Lionel"'
Autor:
Pibre, Lionel, Madrigal, Francisco, Equoy, Cyrille, Lerasle, Frédéric, Pellegrini, Thomas, Pinquier, Julien, Ferrané, Isabelle
Meetings are a common activity in professional contexts, and it remains challenging to endow vocal assistants with advanced functionalities to facilitate meeting management. In this context, a task like active speaker detection can provide useful ins
Externí odkaz:
http://arxiv.org/abs/2206.10411
Publikováno v:
In Fuzzy Sets and Systems 15 January 2025 499
Autor:
Pibre, Lionel
Cette thèse aborde des problèmes liés à la localisation et la reconnaissance d’objets urbains dans des images multi-sources (optique, infrarouge, Modèle Numérique de Surface) de très haute précision acquises par voie aérienne.Les objets ur
Externí odkaz:
http://www.theses.fr/2018MONTS107/document
Since the BOSS competition, in 2010, most steganalysis approaches use a learning methodology involving two steps: feature extraction, such as the Rich Models (RM), for the image representation, and use of the Ensemble Classifier (EC) for the learning
Externí odkaz:
http://arxiv.org/abs/1511.04855
Autor:
Pibre, Lionel, Madrigal, Francisco, Equoy, Cyrille, Lerasle, Frédéric, Pellegrini, Thomas, Pinquier, Julien, Ferrané, Isabelle
Publikováno v:
Multimedia Tools & Applications; Apr2023, Vol. 82 Issue 9, p13667-13688, 22p
Publikováno v:
Proceedings of Meetings on Acoustics; 6/20/2022, Vol. 47 Issue 1, p1-13, 13p
Autor:
Pibre, Lionel
Publikováno v:
Autre [cs.OH]. Université Montpellier, 2018. Français. ⟨NNT : 2018MONTS107⟩
This thesis addresses problems related to the location and recognition of urban objects in multi-source images (optical, infrared, terrain model) of very high precision acquired by air.Urban objects (lamp posts, poles, car, tree...) have dimensions,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______212::b5a1c22268b4aae291fc115f3bdc1092
https://tel.archives-ouvertes.fr/tel-02156868/document
https://tel.archives-ouvertes.fr/tel-02156868/document