1 code implementation • 2 May 2024 • Zhenyang Huang, Zhaojin Fu, Song Jintao, Genji Yuan, Jinjiang Li
We propose MFDS-Net: Multi-Scale Feature Depth-Supervised Network for Remote Sensing Change Detection with Global Semantic and Detail Information (MFDS-Net) with the aim of achieving a more refined description of changing buildings as well as geographic information, enhancing the localisation of changing targets and the acquisition of weak features.
no code implementations • 1 May 2024 • Zhaojin Fu, Zheng Chen, Jinjiang Li, Lu Ren
In addition, in the feature fusion phase, a Feature Refinement and Fusion Block is created to enhance the fusion of different semantic information. We validated the performance of the network using five datasets of varying sizes and types.