基于多路径网络的权值调整图像语义分割算法  

Re-coding semantic image segmentation method based on multi-path network

作　　者：秦晓飞[1] 何玉帅 孙越 严浩通 林轩 QIN Xiaofei;HE Yushuai;SUN Yue;YAN Haotong;LIN Xuan(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093 [2]上海理工大学机械工程学院,上海200093

出　　处：《光学仪器》2020年第1期46-51,共6页Optical Instruments

基　　金：国家重点研究发展计划(2016YFF0101400)。

摘　　要：为提高图像语义分割准确程度,针对场景解析中类别边缘分辨清晰度,提出了一种基于多路径网络的权值调整图像语义分割算法。通过引入多路径网络和权值调整并对图像场景中的物体类别具有的特征进行分析,提高图像的语义分割的准确程度;通过采用ADE20K数据集进行训练,提高边缘信息的分割效果,使模型具有更好的泛化能力。此算法加快了网络收敛速度。In order to improve the accuracy of semantic image segmentation,a semantic segmentation algorithm based on the multi-path network is proposed for the resolution of category edges in scene analysis.By analyzing the characteristics of object classes in image scenes,the idea of the multi-path network and weight adjustment is introduced to improve the accuracy of the algorithm.This paper uses the ADE20K dataset training to significantly improve the segmentation effect.The experimental verification of the public ADE20K dataset proves that compared with the popular image semantic segmentation algorithm,the algorithm has good model convergence ability and generalization ability,and the image edge information segmentation is significantly improved.

关 键 词：图像语义分割 多路径网络 权值调整 边缘信息 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]