SDF2N for VHR Remote Sensing Image Classification

It is the python-keras implementation of the paper: A Shallow-to-Deep Feature Fusion Network for VHR Remote Sensing Image Classification

For more ore information, please see our published paper at IEEE TGRS

Prerequisites

Window 10
Python 3.6
CPU or NVIDIA GPU
CUDA 9.0
Keras 2.2.4

Quick Start

You can run a demo to get started.

python SDF2N_demo.py

Prepare Datasets

Using other dataset mode

In this case, the data structure should be the following:

"""
Image classification data set with pixel-level binary labels；
├─Image
├─Label
├─Train_set
└─Test_set
"""

Citation

If you use this code for your research, please cite our papers.

@ARTICLE{9785804,
  author={Liu, Sicong and Zheng, Yongjie and Du, Qian and Bruzzone, Lorenzo and Samat, Alim and Tong, Xiaohua and Jin, Yanmin and Wang, Chao},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={A Shallow-to-Deep Feature Fusion Network for VHR Remote Sensing Image Classification}, 
  year={2022},
  volume={60},
  number={},
  pages={1-13},
  doi={10.1109/TGRS.2022.3179288}}

Acknowledgments

Our code is inspired by keras-MDFN.