Zobrazeno 1 - 10
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pro vyhledávání: '"Chini, Marco"'
Autor:
Vinholi, João Gabriel, Chini, Marco, Amziane, Anis, Machado, Renato, Silva, Danilo, Matgen, Patrick
In the field of remote sensing, the challenge of comparing images captured by disparate sensors is a common obstacle. This requires image translation -- converting imagery from one sensor domain to another while preserving the original content. Denoi
Externí odkaz:
http://arxiv.org/abs/2404.11243
This paper addresses the challenges of an early flood warning caused by complex convective systems (CSs), by using Low-Earth Orbit and Geostationary satellite data. We focus on a sequence of extreme events that took place in central Vietnam during Oc
Externí odkaz:
http://arxiv.org/abs/2403.14395
Ship detection from satellite imagery using Deep Learning (DL) is an indispensable solution for maritime surveillance. However, applying DL models trained on one dataset to others having differences in spatial resolution and radiometric features requ
Externí odkaz:
http://arxiv.org/abs/2403.13698
Autor:
Krullikowski, Christian, Chow, Candace, Wieland, Marc, Martinis, Sandro, Bauer-Marschallinger, Bernhard, Roth, Florian, Matgen, Patrick, Chini, Marco, Hostache, Renaud, Li, Yu, Salamon, Peter
The Global Flood Monitoring (GFM) system of the Copernicus Emergency Management Service (CEMS) addresses the challenges and impacts that are caused by flooding. The GFM system provides global, near-real time flood extent masks for each newly acquired
Externí odkaz:
http://arxiv.org/abs/2304.12488
Autor:
Brangbour, Etienne, Bruneau, Pierrick, Marchand-Maillet, Stéphane, Hostache, Renaud, Chini, Marco, Matgen, Patrick, Tamisier, Thomas
In this paper, we investigate the conversion of a Twitter corpus into geo-referenced raster cells holding the probability of the associated geographical areas of being flooded. We describe a baseline approach that combines a density ratio function, a
Externí odkaz:
http://arxiv.org/abs/2012.03731
Akademický článek
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Autor:
Brangbour, Etienne, Bruneau, Pierrick, Marchand-Maillet, Stéphane, Hostache, Renaud, Matgen, Patrick, Chini, Marco, Tamisier, Thomas
In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives. From the spatial perspective, our goal here is to get a first estimation of the quality and
Externí odkaz:
http://arxiv.org/abs/1903.04748
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing April 2023 198:99-114
Autor:
Ayoub, Vita, Delenne, Carole, Chini, Marco, Finaud-Guyot, Pascal, Mason, David, Matgen, Patrick, Maria-Pelich, Ramona, Hostache, Renaud
Publikováno v:
In Advances in Water Resources April 2022 162