机械制造与自动化2024，Vol.53Issue(3)：181-184,4.DOI:10.19344/j.cnki.issn1671-5276.2024.03.039
基于改进高分辨率网络的多语义图像分割方法
A Multi Semantic Image Segmentation Method Based on Improved High Resolution Networks
摘要
Abstract
To address the difficulty of image segmentation in complex outdoor scenes,this paper proposes a multi semantic image segmentation model based on HRNet(HR_DfeNet),which optimizes feature extraction by introducing channel attention and spatial attention modules,designs a high-resolution feature extraction branch by improving the pyramid pooling module and ASPP_M module,and integrates with multiple attention mechanisms.On the Cityscape dataset,HR_DfeNet exhibits varying degrees of segmentation optimization performance compared to traditional segmentation models.关键词
室外复杂场景/图像分割/注意力模块/金字塔池化模块Key words
outdoor complex scenes/image segmentation/attention module/pyramid pooling module分类
计算机与自动化引用本文复制引用
张少杰,彭富明,方斌,张子祥,相福磊,何浩天..基于改进高分辨率网络的多语义图像分割方法[J].机械制造与自动化,2024,53(3):181-184,4.基金项目
国家重点研发计划项目(2021YFE0194600) （2021YFE0194600）
江苏省科技计划项目(BZ2023023) （BZ2023023）
