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of 130
pro vyhledávání: '"Castillo-Navarro A"'
Humans perceive the world through multisensory integration, blending the information of different modalities to adapt their behavior. Contrastive learning offers an appealing solution for multimodal self-supervised learning. Indeed, by considering ea
Externí odkaz:
http://arxiv.org/abs/2409.07402
Image-based retrieval in large Earth observation archives is challenging because one needs to navigate across thousands of candidate matches only with the query image as a guide. By using text as information supporting the visual query, the retrieval
Externí odkaz:
http://arxiv.org/abs/2405.03373
Autor:
Mi, Li, Xu, Chang, Castillo-Navarro, Javiera, Montariol, Syrielle, Yang, Wen, Bosselut, Antoine, Tuia, Devis
Cross-view geo-localization aims at localizing a ground-level query image by matching it to its corresponding geo-referenced aerial view. In real-world scenarios, the task requires accommodating diverse ground images captured by users with varying or
Externí odkaz:
http://arxiv.org/abs/2403.13965
Autor:
Mi, Li, Montariol, Syrielle, Castillo-Navarro, Javiera, Dai, Xianjie, Bosselut, Antoine, Tuia, Devis
Asking questions about visual environments is a crucial way for intelligent agents to understand rich multi-faceted scenes, raising the importance of Visual Question Generation (VQG) systems. Apart from being grounded to the image, existing VQG syste
Externí odkaz:
http://arxiv.org/abs/2402.12846
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 6468-6477 (2024)
Deep learning has emerged as a promising avenue for automatic mapping, demonstrating high efficacy in land cover categorization through various semantic segmentation models. Nonetheless, the practical deployment of these models encounters important c
Externí odkaz:
https://doaj.org/article/a36cd00c9c0d4fda8aa90f380ab36771
Autor:
Bolaños-Alvarez, Yoelvis, Ruiz-Fernández, Ana Carolina, Sanchez-Cabeza, Joan-Albert, Asencio, Misael Díaz, Espinosa, Luisa F., Parra, Juan Pablo, Garay, Jesús, Delanoy, Ramón, Solares, Nicolás, Montenegro, Katia, Peña, Alexis, López, Fabiola, Castillo-Navarro, Ana Carolina, Batista, Miguel Gómez, Quejido-Cabezas, Alberto, Metian, Marc, Pérez-Bernal, Libia Hascibe, Alonso-Hernández, Carlos M.
Publikováno v:
In Science of the Total Environment 10 April 2024 920
Publikováno v:
Machines, Vol 12, Iss 9, p 597 (2024)
Renewable energies have a fundamental role in sustainability, with wind power being one of the most important due to its low production costs. Modern wind turbines are becoming bigger and more complex, and their operation and maintenance must be as o
Externí odkaz:
https://doaj.org/article/3f7f58e3e36241da8b35e36c67e9833e
Autor:
Castillo-Navarro, Javiera, Saux, Bertrand Le, Boulch, Alexandre, Audebert, Nicolas, Lefèvre, Sébastien
The development of semi-supervised learning techniques is essential to enhance the generalization capacities of machine learning algorithms. Indeed, raw image data are abundant while labels are scarce, therefore it is crucial to leverage unlabeled in
Externí odkaz:
http://arxiv.org/abs/2010.07830
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