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.

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