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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 rarely exploited as an input information layer. In this paper, we study different use cases anddoi:10.1109/cvprw.2017.199 dblp:conf/cvpr/AudebertSL17 fatcat:yub7f6rsxnadrcj4l2qbzxy6o4