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sar-oil-spill-classifier
osama-bin/sar-oil-spill-classifier
sar-oil-spill-classifier is a machine learning model from osama-bin. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
A CNN + Swin Transformer hybrid deep learning model that classifies oil spill thickness from Sentinel-1 SAR (Synthetic Aperture Radar) images.
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Public
Updated Sep 12, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Sep 12, 2026
- Updated
- Sep 12, 2026
- SHA
- a9428a9c
Model card
From the Hugging Face model README
SAR Oil Spill Thickness Classifier
A CNN + Swin Transformer hybrid deep learning model that classifies oil spill thickness from Sentinel-1 SAR (Synthetic Aperture Radar) images.
What it does
Upload a Sentinel-1 SAR image and the model will:
- Detect oil presence in the SAR image
- Classify the oil thickness into one of three categories:
- Thin_Sheen -- thin oil-sheen-like SAR signature
- Moderate -- intermediate thickness / emulsion
- Thick_Emulsified -- thick or emulsified oil
- Return confidence scores for each class
Model Architecture
| Component | Details |
|---|---|
| CNN Branch | ResNet-18 backbone (512-dim features) |
| Swin Branch | Swin-Tiny patch4 window7 224x224 (768-dim features) |
| Fusion | Concatenation (1280-dim) -> Linear -> BatchNorm -> ReLU (512-dim) |
| Output | Softmax -> 3-class probability distribution |
Usage
Upload any Sentinel-1 SAR image and click Analyse SAR Image.
- License
- mit
- Created
- Sep 12, 2026
- Updated
- Sep 12, 2026