DED-SAM:Adapting Segment Anything Model 2 for Dual Encoder–Decoder Change Detection
Change detection has become a crucial topic in the field of remote sensing deep learning due to its extensive application in earth observation.However, real remote sensing images often contain multiple land cover classes with significant intraclass variability and interclass similarity, limiting the pure energy jeans performance of change detection