Overview
This project utilizes deep learning techniques to detect forest fires using image processing. The model is trained to differentiate between fire and non-fire images, providing an efficient tool for early detection and prevention of wildfires.
Features
Deep Learning-Based Detection: Uses a convolutional neural network (CNN) to classify images.
Jupyter Notebook Implementation: The entire pipeline is implemented in Python using Jupyter Notebook.
Dataset Processing: Handles image preprocessing and augmentation.
Model Training & Evaluation: Includes training scripts, validation, and performance metrics.
Visualization: Displays training progress and predictions.