Fire Classification Models
These Keras models were developed by CPSquad as part of a Deep Learning project for the 1INF52 course at PUCP. We trained them on the FLAME dataset, which provides UAV-based imagery of wildfires.
- DenseNet:
densenet_final.keras - ResNet:
resnet_final.keras - Xception:
xception_final.keras - Ensemble:
ensemble_model.keras
Hyperparameter Tuning
Using Keras Tuner, we optimized:
- Dropout rate
- L2 regularization factor
- Number of layers unfrozen
- Learning rate
These improvements helped boost performance metrics such as accuracy and F1-score, allowing us to reach SOTA results on FLAME’s fire/no-fire classification task.
GitHub repo: https://github.com/superflash41/isaFIRE-wildifire-detection-project
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