Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3

doi:10.1007/s11633-020-1269-5

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3
	Yue-Yan Qin 2
刊名	International Journal of Automation and Computing
	2021
卷号	18 期号:2 页码:300-310
关键词	Fire detection depthwise separable convolution fire classification You Only Look Once version 3 (YOLOv3) target regression
ISSN号	1476-8186
DOI	10.1007/s11633-020-1269-5
英文摘要	Recently, video-based fire detection technology has become an important research topic in the field of machine vision. This paper proposes a method of combining the classification model and target detection model in deep learning for fire detection. Firstly, the depthwise separable convolution is used to classify fire images, which saves a lot of detection time under the premise of ensuring detection accuracy. Secondly, You Only Look Once version 3 (YOLOv3) target regression function is used to output the fire position information for the images whose classification result is fire, which avoids the problem that the accuracy of detection cannot be guaranteed by using YOLOv3 for target classification and position regression. At the same time, the detection time of target regression for images without fire is greatly reduced saved. The experiments were tested using a network public database. The detection accuracy reached 98% and the detection rate reached 38 fps. This method not only saves the workload of manually extracting flame characteristics, reduces the calculation cost, and reduces the amount of parameters, but also improves the detection accuracy and detection rate.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/44024]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.School of Automation, Shenyang Aerospace University, Shenyang 110136, China 2.School of Information and Control Engineering, Liaoning Shihua University, Fushun 113001, China
推荐引用方式 GB/T 7714	Yue-Yan Qin. Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3[J]. International Journal of Automation and Computing,2021,18(2):300-310.
APA	Yue-Yan Qin.(2021).Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3.International Journal of Automation and Computing,18(2),300-310.
MLA	Yue-Yan Qin."Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3".International Journal of Automation and Computing 18.2(2021):300-310.