MARRYING DEEP LEARNING AND DATA FUSION FOR ACCURATE SEMANTIC LABELING OF SENTINEL-2 IMAGES
The understanding of the Earth through global land monitoring from satellite images paves the way towards many applications including flight simulations, urban management and telecommunications. The twin satellites from the Sentinel-2 mission developed by the European Space Agency (ESA) provide 13 s...
Main Authors: | G. Fonteix, M. Swaine, M. Leras, Y. Tarabalka, S. Tripodi, F. Trastour, A. Giraud, L. Laurore, J. Hyland |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2021-06-01
|
Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-3-2021/101/2021/isprs-annals-V-3-2021-101-2021.pdf |
Similar Items
-
OPERATIONAL PIPELINE FOR A GLOBAL CLOUD-FREE MOSAIC AND CLASSIFICATION OF SENTINEL-2 IMAGES
by: M. Swaine, et al.
Published: (2020-08-01) -
BRIGHTEARTH: PIPELINE FOR ON-THE-FLY 3D RECONSTRUCTION OF URBAN AND RURAL SCENES FROM ONE SATELLITE IMAGE
by: S. Tripodi, et al.
Published: (2022-05-01) -
Deep Semantic Hashing Using Pairwise Labels
by: Richeng Xuan, et al.
Published: (2021-01-01) -
A Semantic Labeling Approach for Accurate Weed Mapping of High Resolution UAV Imagery
by: Huasheng Huang, et al.
Published: (2018-07-01) -
Fusion of sentinel-1 SAR and sentinel-2 MSI data for accurate Urban land use-land cover classification in Gondar City, Ethiopia
by: Shimelis Sishah Dagne, et al.
Published: (2023-11-01)