---
language: "en"
library_name: "keras"
tags:
- image-classification
- fire-detection
license: "mit"
datasets:
- flame
metrics:
- accuracy
- f1
model_creator: "CPSquad"
course: "1INF52 (PUCP)"
---

# 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](https://keras.io/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.