The Multi-Scale Depth-Separable Convolution Network for Fire and Smoke Detection

IF 1.7 4区工程技术 Q4 ENERGY & FUELS

Combustion Science and Technology Pub Date : 2024-07-05 DOI:10.1080/00102202.2024.2372689

Huihui Yan, Zhihua Cui, Haotian Zhao, Jingbo Zhang, Juanjuan Qin, Qian Guo

引用次数: 0

Abstract

Fire is one of the major disasters threatening public safety and social development. The existing methods have made some advancements in the fire and smoke detection but still face several challeng...

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用于烟火探测的多尺度深度可分离卷积网络

火灾是威胁公共安全和社会发展的主要灾害之一。现有的方法在火灾和烟雾探测方面取得了一些进展，但仍面临一些挑战...

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来源期刊

Combustion Science and Technology 工程技术-工程：化工

CiteScore

4.10

自引率

10.50%

发文量

182

审稿时长

8.3 months

期刊介绍： Combustion Science and Technology is an international journal which provides for open discussion and prompt publication of new results, discoveries and developments in the various disciplines which constitute the field of combustion. The editors invite original contributions dealing with flame and fire research, flame radiation, chemical fuels and propellants, reacting flows, thermochemistry, material synthesis, atmospheric chemistry and combustion phenomena related to aircraft gas turbines, chemical rockets, ramjets, automotive engines, furnaces and environmental studies. In so doing, the editors hope to establish a central vehicle for the rapid exchange of ideas and results emanating from the many diverse areas associated with combustion. Accordingly, both full-length papers on comprehensive studies, and communications of significant, but not fully explored, theoretical or experimental developments are included in the journal together with unsolicited and solicited comments on published matter and yearly, cumulative indices.