Awesome
<div align="center"> <h1> SITSMamba for Crop Classification based on <br /> Satellite Image Time Serie</h1>Xiaolei Qin, Xin Su, Liangpei Zhang
<a href="https://arxiv.org/abs/2409.09673"><img src="https://img.shields.io/badge/arxiv_Paper-%23808EDC"></a>
</div>:snake:Highlight
SITSMamba adopts Mamba for Satellite image time series classification for the first time.
<figure> <div align="center"> <img src=Pics/Architecture.jpg width="90%"> </div> </figure>:ear_of_rice:Dataset
PASTIS<br /> All the 20 classes are used for training and evaluation in our study. <br /> MTLCC<br /> All the 17 classes are used for training and evaluation in our study. <br />
:hammer:Environment
You can install mamba according to the following instruction.
conda create -n mamba python==3.8
pip install torch==2.2.1 torchvision==0.17.1 --index-url https://download.pytorch.org/whl/cu121
wget https://github.com/state-spaces/mamba/releases/download/v1.2.2/mamba_ssm-1.2.2+cu122torch2.2cxx11abiFALSE-cp38-cp38-linux_x86_64.whl
pip install mamba_ssm-1.2.2+cu122torch2.2cxx11abiFALSE-cp38-cp38-linux_x86_64.whl
:blue_heart:Thanks
The ConvBlock is from UTAE. The temporal encoder, Mamba block, is from mamba.