Mango-Mars/MF-Mamba
Domain:
geospatialRecord type:
modelsoftware
Creator:
Man
Host:
# MF-Mamba: Multiscale Convolution and Mamba Fusion Model for Semantic Segmentation of Remote Sensing Imagery
This is an official implementation of MF-Mamba in our TGRS 2025 paper "MF-Mamba: Multiscale Convolution and Mamba Fusion Model for Semantic Segmentation of Remote Sensing Imagery".
## Main Environments
```
conda create -n MFMamba python=3.8
conda activate MFMamba
pip install torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 --index-url download.pytorch.org
pip install causal_conv1d==1.0.0
pip install mamba_ssm==1.0.1
```
If problems occur during installation, the corresponding precompiled package can be downloaded and used for installation. Refer to causal-conv1d and mamba-ssm.
## Pretrained weights
We use the ImageNet pretrained HRNet-W18-C model 'hrnetv2_w18_imagenet_pretrained.pth' from HRNets.
## Citation
If you find it useful, please consider citing:
```
@ARTICLE{11098811,
author={Xiao, Pu and Dong, Yuting and Zhao, Ji and Peng, Tieqi and Geiß, Christian and Zhong, Yanfei and Taubenböck, Hannes},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={MF-Mamba: Multiscale Convolution and Mamba Fusion Model for Semantic Segmentation of Remote Sensing Imagery},
year={2025},
}
```