https://github.com/vbhavank/Unstructured-change-detection-using-CNN

Unstructured Change detection in satellite imagery
https://github.com/vbhavank/Unstructured-change-detection-using-CNN

aerial-imagery computer-vision machine-learning neural-networks remote-sensing

Last synced: about 1 month ago
JSON representation

Unstructured Change detection in satellite imagery

• Host: GitHub
• URL: https://github.com/vbhavank/Unstructured-change-detection-using-CNN
• Owner: vbhavank
• License: gpl-3.0
• Created: 2018-04-24T03:14:39.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-03-02T19:01:41.000Z (over 4 years ago)
• Last Synced: 2024-02-17T14:36:20.936Z (5 months ago)
• Topics: aerial-imagery, computer-vision, machine-learning, neural-networks, remote-sensing
• Language: Python
• Homepage:
• Size: 719 KB
• Stars: 59
• Watchers: 8
• Forks: 27
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-remote-sensing-change-detection - El Amin A M, Liu Q, Wang Y. Convolutional neural network features based change detection in satellite images

README

        
# Unstructured-change-detection-using-CNN

This repository contains implementation of the paper 'Mohammed El Amin, Arabi & Liu, Qingjie & Wang, Yunhong. (2016). Convolutional neural network features based change detection in satellite images. 100110W. 10.1117/12.2243798'.  

# Instrustion to run the file

The feat.py file accepts the two file paths corresponding to the two input patches as arguments.

For example to find Unstructured change in two image patches img1.PNG and img2.PNG, both located in the ./data/ folder by running

$ python feat.py ./data/img1.PNG ./data/img2.PNG