HARNESSING DEEP LEARNING FOR WILDFIRE RISKS PREDICTION: A NOVEL APPROACH

This article presents a pioneering approach for predicting wildfires risks using deep learning techniques. By combining convolutional neural networks (CNNs), recurrent neural networks (RNNs) and Adaptive Moment Estimation (ADAM), our framework analyses geospatial and environmental data to capture th...

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