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Valérie Gouet-Brunet
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Documents
Identifiants chercheurs
- valerie-gouet-brunet
- 0000-0003-3666-5146
- IdRef : 174365020
Présentation
**Research director (DR1, French Ministry of Ecology)**
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**IGN - Université Gustave Eiffel, LASTIG Lab.**
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IGN-ENSG, F-94160 Saint-Mande, France
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Valérie Gouet-Brunet is research director of the French Ministry of Ecology and carries out her research in the research department of the French mapping agency (IGN) and the Gustave Eiffel University, within the LaSTIG laboratory. There, she is in charge of researches on the description by content, matching, structuring and indexing of large-scale multimedia collections, with a focus on images. Until 2018, she has headed the IGN's MATIS laboratory (35 members) for 4 years, specialized in mathematics and computer science applied to photogrammetry, computer vision and remote sensing for multi-sensor and multi-source imaging. She obtained a PhD in Computer Vision in 2000 from the University of Montpellier II (France) on the area of color image matching with application to intermediate view synthesis, and an habilitation to conduct research at the Pierre and Marie Curie University (France) in 2008 on the area of content-based structuring of collections of still and animated images.
Her main research areas concern the matching and large-scale indexing of multi-date and multi-source images, currently with the main objectives of image collections interlinking and image-based localization, for the application fields of iconographic heritage promotion and embedded navigation. V. Gouet-Brunet has supervised more than fifty researchers and participated in or coordinated some twenty partnership projects of various kinds (national ANR and FUI projects, European projects, bilateral industrial contracts, international research collaborations) on these themes. She is currently coordinating the ALEGORIA project (French ANR 2017), is a member of the steering committee of the European project CSA Time Machine, and member of the board of the Time Machine Organisation.
Publications
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Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imageryISPRS Journal of Photogrammetry and Remote Sensing, 2017, 126, pp.129-145. ⟨10.1016/j.isprsjprs.2017.02.011⟩
Article dans une revue
hal-02338242v1
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Forest stand extraction: which optimal remote sensing data source(s)?IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2018, Valencia, Spain
Communication dans un congrès
hal-02368554v1
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Semantic segmentation of forest stands of pure species as a global optimization problemISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, Hannover, France. pp.141-148, ⟨10.5194/isprs-annals-IV-1-W1-141-2017⟩
Communication dans un congrès
hal-02367562v1
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How to combine LIDAR and very high resolution multispectral images for forest stand segmentation?IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2017, Fort Worth, United States
Communication dans un congrès
hal-02368527v1
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Segmentation sémantique de données de télédétection multimodale: application aux peuplements forestiersORASIS 2017, GREYC, Jun 2017, Colleville-sur-Mer, France
Communication dans un congrès
hal-01866680v1
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Forest stand segmentation using airborne Lidar data and very high resolution multispectral imageryInternational Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Jul 2016, Prague, Czech Republic. pp.207-214, ⟨10.5194/isprs-archives-XLI-B3-207-2016⟩
Communication dans un congrès
hal-02366424v1
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