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license: mit |
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# MobileNetWildFireModel for Wildfire Classification |
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## Model Details |
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- **Model Architecture:** MobileNetV2 (Modified) |
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- **Framework:** PyTorch |
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- **Input Shape:** 3-channel RGB images |
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- **Number of Parameters:** ~3.4M (Based on MobileNetV2) |
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- **Output:** Binary classification (wildfire presence) |
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## Model Description |
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This model is a **fine-tuned MobileNetV2** for wildfire classification. The pretrained **MobileNetV2** backbone is used with its feature extractor **frozen**, while only the **final classification layer** is trained. The last fully connected layer has been replaced with a **single output neuron** for binary classification, predicting the presence of wildfire. |
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## Training Details |
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- **Optimizer:** Adam |
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- **Batch Size:** 32 |
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- **Loss Function:** Binary Cross-Entropy (BCE) |
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- **Number of Epochs:** 10 |
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- **Dataset:** [Wildfire Detection Image Data](https://www.kaggle.com/datasets/brsdincer/wildfire-detection-image-data) |
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### Losses Per Epoch |
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| Epoch | Training Loss | Validation Loss | |
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|-------|---------------|-----------------| |
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| 1 | 0.0991 | 0.0255 | |
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| 2 | 0.0046 | 0.0269 | |
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| 3 | 0.0038 | 0.0290 | |
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| 4 | 0.0026 | 0.0227 | |
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| 5 | 0.0023 | 0.0229 | |
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| 6 | 0.0019 | 0.0291 | |
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| 7 | 0.0020 | 0.0269 | |
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| 8 | 0.0017 | 0.0230 | |
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| 9 | 0.0015 | 0.0243 | |
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| 10 | 0.0014 | 0.0241 | |
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## License |
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This model is released under the **MIT License**. |
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