Official_Remote_Sensing_Mamba
The RS-Mamba project features an innovative Recurrent State Space Model designed for dense prediction in large remote sensing images. By utilizing a state space model for the first time in this context, RS-Mamba achieves an effective global receptive field with linear complexity, setting new standards in semantic segmentation and change detection. This model is structured to optimally map spatial features across various directions, ensuring efficiency and power even with straightforward training methods. Explore the code and documentation to enhance remote sensing projects.
