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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 data classification from various sensors, including multispectral, hyperspectral, SAR and LiDAR data. While OpenStreetMap has already been used as ground truth data for training such networks, this abundant data source remains...
The increasing availability of very-high-resolution (VHR) aerial optical images as well as coregistered Li- DAR data opens great opportunities for improving objectlevel dense semantic labeling of airborne remote sensing imagery. As a result, efficient and effective multisensor fusion techniques are needed to fully exploit these complementary data modalities. Recent researches demonstrated how to process...
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