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IRCNN

This repository includes codes and dataset for "IRCNN:An Irregular-Time-Distanced Recurrent Convolutional Neural Network for Change Detection in Satellite Time Series", which has been published in IEEE Geoscience and Remote Sensing Letters.

Paper Link: https://ieeexplore.ieee.org/document/9721897
Paper DOI: 10.1109/LGRS.2022.3154894

The materials in this repository are only for study and research, NOT FOR COMMERCIAL USE. Please cite this paper if it is helpful for you.


Requirements:

 cuda 10.0  
 numpy 1.19  
 pandas 1.1  
 python 3.6  
 pytorch 1.8.1  

Data preparation

The shape of the input data : (T, B, C, H, W)
 T is the length of Time
 B is the Batch size
 C is the Channels
 H is the High of the image patch
 W is the Width of the image patch

Train

python train.py
Note there is a config file named Parameter.yaml

Test

python test.py

Data Download

Remote sensing images (Landast7/8) and ground truth map of five study areas:
Access from Baidu Cloud
Link: https://pan.baidu.com/s/1UhE0N2GcybyjZdIYb8TlGQ
Password: wdzm
Access from Google Drive
Link: https://drive.google.com/drive/folders/1DeJqrVz5luVcwCs-zknvQBY85Ks4X0WP?usp=sharing

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IRCNN:An Irregular-Time-Distanced Recurrent Convolutional Neural Network for Change Detection in Satellite Time Series

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