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What is Forest Fire Detection with CNNs about?

The paper proposes a forest fire detection system using a convolutional neural network. The system processes videos frame-by-frame to detect anomalies in real-time and alert authorities. The model detects forest fires at 45 frames per second with 89.3% accuracy on the IMFDB dataset, 82.6% on the UGR dataset, and 86.5% on the FireNet dataset. The system architecture includes modules for video input, preprocessing, feature extraction using a CNN, and fire detection output. The CNN is trained on 3000 fire imag

Author

Soundarya

Language

EN