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Found 2 papers, 1 papers with code
Hidden Path Selection Network for Semantic Segmentation of Remote Sensing Images
Targeting at depicting land covers with pixel-wise semantic categories, semantic segmentation in remote sensing images needs to portray diverse distributions over vast geographical locations, which is difficult to be achieved by the homogeneous pixel-wise forward paths in the architectures of existing deep models.
Semantic Change Detection with Asymmetric Siamese Networks
Given two multi-temporal aerial images, semantic change detection aims to locate the land-cover variations and identify their change types with pixel-wise boundaries.
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