现代电子技术2025，Vol.48Issue(2)：179-186,8.DOI:10.16652/j.issn.1004-373x.2025.02.028
基于语义分割的乡村道路识别
Rural road recognition based on semantic segmentation
摘要
Abstract
In allusion to the problem of insufficient recognition accuracy of surrounding features when intelligent agricultural machinery drives in complex rural environments,an improved PP-LiteSeg model is proposed based on rural road scenes as the research object.The STDC is used to extract features from the image,which can ensure the completeness of the feature information while ensuring the lightweight.The strip pooling is introduced into a simple pyramid module to enhance feature extraction capabilities.The coordinate attention is integrated into the unified attention fusion module to further enhance the fusion of multi-scale features and capture richer information,thereby improving the accuracy of the model in recognizing complex rural scenes.The experiments show that the model can realize better segmentation results in different scenes,and the accuracy rate of individual categories such as buildings,asphalt roads,and obstacles can reach more than 80%,which has can effectively segment the rural road scene.The improved model can provide technical references for the intelligent agricultural machine to drive safely in the rural road scene.关键词
语义分割/乡村道路/特征识别/条形池化/坐标注意力/场景分类/图像处理Key words
semantic segmentation/rural road/feature recognition/strip pooling/coordinate attention/scene classification/image process分类
信息技术与安全科学引用本文复制引用
曹新宇,张太红,赵昀杰,姚芷馨..基于语义分割的乡村道路识别[J].现代电子技术,2025,48(2):179-186,8.基金项目
科技创新2030—"新一代人工智能"重大项目(2022ZD0115805) （2022ZD0115805）
新疆维吾尔自治区重大科技专项:农场数字化及智能化关键技术研究(2022A02011) （2022A02011）
