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Road Segmentation for Remote Sensing Images using Adversarial Spatial Pyramid Networks
[article]
2020
arXiv
pre-print
Road extraction in remote sensing images is of great importance for a wide range of applications. Because of the complex background, and high density, most of the existing methods fail to accurately extract a road network that appears correct and complete. Moreover, they suffer from either insufficient training data or high costs of manual annotation. To address these problems, we introduce a new model to apply structured domain adaption for synthetic image generation and road segmentation. We
arXiv:2008.04021v1
fatcat:rrxxun2eqbfjbajznlgwrtvdqq