An Analysis of Parameters of Convolutional Neural Network for Fire Detection

In this paper, a deep learning method is proposed to detect fire effectively using video of surveillance camera. Based on AlexNet model, classification performance is compared according to kernel size and stride of convolution layer. Dataset for learning and inference are classified into two classes as normal and fire. Normal images include clouds and foggy and fire images include smoke and flames, respectively. As results of simulations, it is shown that the larger kernel size and smaller stride shows better performance.

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