Forest Fire Recognition Based on Deep Convolutional Neural Network Under Complex Background

doi:10.3969/j.issn.1006-2475.2016.03.011

Abstract

Abstract: According to the characteristics of forest fire, a forest fire image recognition method based on deep learning is proposed and designed. The structure of convolutional neural network (CNN) is given by experiment, which is used in forest fire recognition under the complex background, and it has been trained and tested. A parameters replacement method is presented for low recognition rate existing in small samples forest fire recognition. The results show that the method is of a high accuracy reaching to 98%, it can extract features automatically, the input image doesn’t need to pre-processing, and it overcomes many inherent shortcomings of traditional algorithm. Its application in the field of forest fire recognition achieves good results.

Key words: image processing, forest fire recognition, deep learning, convolutional neural network

CLC Number:

TP391

FU Tian-ju, ZHENG Chang-e, TIAN Ye, QIU Qi-min, LIN Si-jun. Forest Fire Recognition Based on Deep Convolutional Neural Network Under Complex Background[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.03.011.

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