readme.md

ACRNet(Published in IEEE-GRSL 2021): Multilevel Feature Fusion Networks With Adaptive Channel Dimensionality Reduction for Remote Sensing Scene Classification

Xin Wang , Lin Duan , Aiye Shi , Huiyu Zhou

Multilevel Feature Fusion Networks With Adaptive Channel Dimensionality Reduction for Remote Sensing Scene Classification[Paper link]

Usage

1. Data preparation: split.py

dataset|——train
	   |——Airport
	   |——BareLand
	   |——....
	   |——Viaduct
       |——val
	   |——Airport
	   |——BareLand
	   |——....
	   |——Viaduct

2. run train.py to train the model
3. confusionmatrix.py for drawing

Figs

Datasets:

UC Merced Land Use Dataset:

http://weegee.vision.ucmerced.edu/datasets/landuse.html

AID Dataset:

https://captain-whu.github.io/AID/

NWPU RESISC45:

http://www.escience.cn/people/JunweiHan/NWPU-RESISC45.html

Environments

1. Ubuntu 16.04
2. cuda 10.0
3. pytorch 1.0.1
4. opencv 3.4

Citation

Please cite our paper if you find the work useful:

@ARTICLE{9399658,
 author={Wang, Xin and Duan, Lin and Shi, Aiye and Zhou, Huiyu},
 journal={IEEE Geoscience and Remote Sensing Letters},
 title={Multilevel Feature Fusion Networks With Adaptive Channel Dimensionality Reduction for Remote Sensing Scene Classification},
 year={2021},
 volume={}, 
 number={}, 
 pages={1-5}, 
 doi={10.1109/LGRS.2021.3070016}}