HegdeSudarshan/BigEarthNetModels

BigEarthNet Super-Resolution + Active Learning Classifier

This application enhances satellite images using Super-Resolution and classifies them into 43 land cover types.

Features

• —Super-Resolution: 4× upscaling (30×30 → 120×120) using RFB-ESRGAN
• —Multi-label Classification: 43 BigEarthNet V2 land cover classes
• —Active Learning: Trained efficiently using DBSS + SSAS strategies

Models

• —SR Generator: RFB-ESRGAN with 6 RRDB + 6 RFB blocks
• —Classifier: ResNet-18 backbone with multi-label head

Usage

1. 1.Upload a satellite image (RGB)
2. 2.View the enhanced SR image
3. 3.See top 5 predicted land cover classes

Dataset

Trained on BigEarthNet V2 - Sentinel-2 satellite imagery dataset.

Citation

If you use this model, please cite:

@inproceedings{bigearthnet,
  title={BigEarthNet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding},
  author={Sumbul, Gencer and Charfuelan, Marcela and Demir, Begum and Markl, Volker},
  booktitle={IEEE International Geoscience and Remote Sensing Symposium},
  year={2019}
}

License

MIT License