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High-resolution semantically-consistent image-to-image translation. (arXiv:2209.06264v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Deep learning has become one of remote sensing scientists' most efficient
computer vision tools in recent years. However, the lack of training labels for
the remote sensing datasets means that scientists need to solve the domain
adaptation problem to narrow the discrepancy between satellite image datasets.
As a result, image segmentation models that are then trained, could better
generalize and use an existing set of labels instead of requiring new ones.
This work proposes an unsupervised domain adaptation model that …