Niharmahesh/data298A

LEVIR-CD and S2Looking Combined Dataset

Description

This dataset is a combination of two popular change detection datasets: LEVIR-CD and S2Looking. The images have been chipped to create a more comprehensive and diverse dataset for change detection tasks.

Dataset Details

• Source Datasets:

  1. LEVIR-CD (Land-cover change detection dataset for remote sensing images)
  2. S2Looking (A large-scale dataset for bi-temporal remote sensing image change detection)

• Preprocessing: The original images from both datasets have been chipped into smaller segments to facilitate easier processing and analysis.

Usage

This combined and chipped dataset is designed for:

• Change detection in remote sensing imagery
• Training and evaluating machine learning models for bi-temporal image analysis
• Benchmarking change detection algorithms

License

MIT License

Copyright (c) [Year] [Full name]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Acknowledgements

We would like to acknowledge the creators of the original LEVIR-CD and S2Looking datasets for their valuable contributions to the remote sensing community.