HIGHLIGHTS
SUMMARY
I at different times. The first method is to treat CD as a dense prediction task similar to image segmentation and introduce image segmentation models such as U-Net for improvement, which using the encoder extracts bitemporal features, and the decoder fuses the bitemporal features to generate a change map. Previous studies have mainly focused on using CNNs to mine the relationship between bitemporal images to obtain more discriminative features. If the extracted features already contain rich changing information such as the positions of changed objects and unchanged objects, the change map can be . . .
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