A Deep Flame and Smoke Visual Detection Modol Research By Fusing Multi-Scale Features
To accurately detecting flame and smoke simultaneously,we fuse and enhance features to propose a deep visual fire detection network.On the basis of a multi-scale feature backbone network,we design a high-level semantic spatial information enhancement module,a multi-scale feature depth fusion module,a spatial distance information attention module,and a classification and positioning module.These modules mainly focus on extracting spatial textures and multi-scale features of flame and smoke,and detecting small objects of flame and smoke.We participated in constructing a new flame and smoke detection dataset for training and testing visual fire detection models.Experimental results show that our method achieves better results than the compared methods.
Fire DetectionFlame DetectionSmoke DetectionFeature EnhancementObject Detection
NETL
NSTL
万方数据
