Automatic classification system of fires and smokes from the delta area in Egypt using neural networks

Abstract EN

An automatic system has been designed to classify fires and smokes from the Delta area in Egypt using Neural Networks (NNs).

The proposed system is trained on the features of the provided image, and is designed to work in an automatic way for finding the best network that has the ability to have the best classification on data is not included in the training data.

It is applied with varying number of layers and neurons in the hidden layers to determine the optimum network architecture.

The system shows an excellent classification of the specified features, the obtained performance is 100% for test data that was collected from the training data, while is 99.6% for test data that was not included in the training data.

The designed system can be carried out on remotely sensed images for classifying any other features.