A. Fernandes, Andrei Borissovitch Utkin, Paulo Chaves
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引用次数: 1
Abstract
The ability of EfficientDet, a framework developed in 2019 for object detection, to automatically detect smoke plumes at a distance of several kilometers is demonstrated. Recent articles have raised concerns about the effectiveness of EfficientDet in fire detection applications, with over 40% of false positives reported. The proposed EfficientDet model achieved a true detection rate of 80.4% and a false-positive rate of 1.13% on a testing set. The data set used in this study, which includes 14,125 smoke and 21,203 non-smoke images, is one of the largest, or even the largest, of its kind reported in the literature for images containing smoke plumes. Our results surpass those of a previous study that used the same data set and are more reliable and realistic than those reported by others, which may seem better, but were calculated using smaller and less representative data sets.
期刊介绍:
The Journal of Fire Sciences is a leading journal for the reporting of significant fundamental and applied research that brings understanding of fire chemistry and fire physics to fire safety. Its content is aimed toward the prevention and mitigation of the adverse effects of fires involving combustible materials, as well as development of new tools to better address fire safety needs. The Journal of Fire Sciences covers experimental or theoretical studies of fire initiation and growth, flame retardant chemistry, fire physics relative to material behavior, fire containment, fire threat to people and the environment and fire safety engineering. This journal is a member of the Committee on Publication Ethics (COPE).