湖北民族大学学报（自然科学版）2025，Vol.43Issue(3)：357-361,369,6.DOI:10.13501/j.cnki.42-1908/n.2025.09.014
融合注意力机制与边缘引导的MA-PSPNet工地作业场景语义分割模型
Integrated Attention Mechanism and Edge-guided Semantic Segmentation MA-PSPNet Model for Construction Site Scenes
摘要
Abstract
To enhance the semantic segmentation accuracy of safety helmets in complex scenarios and address issues involving blurred edges,poor segmentation of small objects,and multi-scale variations,a multi-scale attention pyramid scene parsing network(MA-PSPNet)model for construction site scenes integrated with attention mechanism and edge guidance was developed.In the proposed architecture,a multi-scale convolutional attention(MSCA)module was embedded within the feature extraction backbone network of the model to enhance feature representation in critical regions.An edge-guided attention(EGA)module was incorporated subsequently to the second-stage feature extraction backbone network to refine boundary identification capabilities.Furthermore,the pyramid pooling structure of the pyramid scene parsing network(PSPNet)was replaced by an atrous spatial pyramid pooling module to strengthen multi-scale adaptation.The results showed that the mean intersection over union of MA-PSPNet model was 83.28%,with an improvement of 9.13 percentage points compared to the original PSPNet model.The pixel accuracy and mean pixel accuracy were quantified at 95.62%and 88.74%,respectively.MA-PSPNet model could enhance effectively safety helmet segmentation precision and boundary awareness within complex industrial environments and had good practicality.关键词
安全帽分割/语义分割/注意力机制/边缘引导/多尺度增强Key words
safety helmet segmentation/semantic segmentation/attention mechanism/edge guidance/multi-scale enhancement分类
信息技术与安全科学引用本文复制引用
陈慧,王涛..融合注意力机制与边缘引导的MA-PSPNet工地作业场景语义分割模型[J].湖北民族大学学报（自然科学版）,2025,43(3):357-361,369,6.基金项目
安徽省重点研究与开发计划项目(2023AH051586). （2023AH051586）
