9 citations · 17 across the 2 of their papers we have counts for
3 papers
Deep learning for semantic segmentation of remote sensing images with rich spectral content
A Hamida, A. Benoît, P. Lambert +4
With the rapid development of Remote Sensing acquisition techniques, there is a need to scale and improve processing tools to cope with the observed increase of both data volume an…
Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks
Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre
In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolution…
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps
Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre
In this work, we investigate the use of OpenStreetMap data for semantic labeling of Earth Observation images. Deep neural networks have been used in the past for remote sensing dat…