Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- CNRS
- Nature Careers
- Ecole Nationale de l'Aviation Civile
- Ecole Normale Superieure
- Ecole normale supérieure - PSL
- Gisèle Krysztofiak
- INSA Strasbourg
- Inria, the French national research institute for the digital sciences
- Institut Curie - Research Center
- Sorbonne Université SIS (Sciences, Ingénierie, Santé)
- Télécom Paris
- University of Tours
- Université Clermont Auvergne
- Université Grenoble Alpes
- Université de Technologie de Troyes
- Université du Littoral Côte d'Opale
- 6 more »
- « less
-
Field
-
surveys, soil chemistry, paleoarchives, LiDAR point cloud); • Analysis of ex-situ fire experiments, particularly regarding nutrient losses and vegetation functional responses; • Field participation in
-
deposition. Aging processes—such as surface coating, interaction with secondary aerosols, and changes in hygroscopicity—will be incorporated to better represent cloud interactions and removal processes. Model
-
Agriculture: Natural Language Interfaces over Robotic and Analytical Farming Systems In the context of the MSCA JD project GreenFieldData https://www.eu4greenfielddata.eu/ GreenFieldData: IoRT Data Management
-
, technicians, and administrative staff across three sites: Paris, Orsay, and Saint-Cloud. The institute's facilities include an advanced imaging platform with a wide variety of high-end microscopes, from
-
and density of all gas clouds, the local magnetic and radiation fields. Second, we will study the impact of the SNR on the local star formation (SF). To this aim, we will use high angular resolution
-
and heritage corpora into immersive environments and, ultimately, into the Cultural Heritage Cloud (ECCCH) developed by the ECHOES project. She/he will be responsible for the technical design and
-
machine coding. Augmented and virtual reality applications, 360° video, point clouds, and advanced representations such as Gaussian Splatting require a rethinking of compression models to take into account
-
between complex instances such as point clouds, images or graphs. However, as the modern data are increasingly high-dimensional, OT is also now facing an old problem in optimization and statistical learning
-
measurements by LiDAR and images. While images are dense 2D grids, point clouds made by LiDARs are sparse and unstructured. This difference gives rise to the central question of LiDAR-camera fusion, that is to