13 citations · 28 across the 4 of their papers we have counts for
6 papers
FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping
Anatol Garioud, Sébastien Giordano, Nicolas David +1
The growing availability of high-quality Earth Observation (EO) data enables accurate global land cover and crop type monitoring. However, the volume and heterogeneity of these dat…
FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery
Anatol Garioud, Nicolas Gonthier, Loic Landrieu +5
We introduce the French Land cover from Aerospace ImageRy (FLAIR), an extensive dataset from the French National Institute of Geographical and Forest Information (IGN) that provide…
FLAIR #2: textural and temporal information for semantic segmentation from multi-source optical imagery
Anatol Garioud, Apolline De Wit, Marc Poupée +3
The FLAIR #2 dataset hereby presented includes two very distinct types of data, which are exploited for a semantic segmentation task aimed at mapping land cover. The data fusion wo…
FLAIR #1: semantic segmentation and domain adaptation dataset
Anatol Garioud, Stéphane Peillet, Eva Bookjans +2
The French National Institute of Geographical and Forest Information (IGN) has the mission to document and measure land-cover on French territory and provides referential geographi…
Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention
Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano +1
Satellite image time series, bolstered by their growing availability, are at the forefront of an extensive effort towards automated Earth monitoring by international institutions.…
Time-Space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series
Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano +1
In this article, we investigate several structured deep learning models for crop type classification on multi-spectral time series. In particular, our aim is to assess the respecti…