深度学习实时语义分割算法研究综述  

Review of Real-Time Semantic Segmentation Algorithms for Deep Learning

作　　者：何家峰[1] 陈宏伟 骆德汉[1] HE Jiafeng;CHEN Hongwei;LUO Dehan(School of Information Engineering,Guangdong University of Technology,Guangzhou 511400,China)

机构地区：[1]广东工业大学信息工程学院,广州511400

出　　处：《计算机工程与应用》2023年第8期13-27,共15页Computer Engineering and Applications

基　　金：国家自然科学基金(61571140)。

摘　　要：语义分割是从像素的角度分割出图片中的不同对象,并对原始图片中的每个像素进行标注的一种技术。但由于无人机导航、遥感图像、医疗诊断等应用领域需要实时地进行语义分割处理。所以,基于深度学习的实时语义分割技术得到了迅速的发展。实时语义分割技术发展至今已有许多的技术与模型。基于此,在对相关文献进行研究的基础上,由语义分割技术引出了实时语义分割技术,并简单叙述了实时语义分割的优点。随后,研讨出目前实时语义分割存在的重难点。根据重难点进而对已存在的相关技术与模型进行阐述,并总结技术与模型的优缺点。最后,展望实时语义分割所面临的挑战,并对实时语义分割进行了总结与归纳,为后续的研讨提供了一些理论参考。Semantic segmentation is a technique to segment different objects in a picture from the perspective of pixels and label each pixel in the original picture.However,due to UAV navigation,remote sensing images,medical diagnosis and other application fields,real-time semantic segmentation is needed.Therefore,the real-time semantic segmentation technology based on deep learning has developed rapidly.There are many technologies and models for real-time semantic segmentation.Based on this,on the basis of studying the related literature,the real-time semantic segmentation technology is introduced by semantic segmentation technology,and the advantages of real-time semantic segmentation are briefly described.Then,the important and difficult points of real-time semantic segmentation are discussed.According to the important and difficult points,the existing related technologies and models are expounded,and the advantages and disad-vantages of the technologies and models are summarized.Finally,the challenges faced by real-time semantic segmenta-tion are prospected,and the real-time semantic segmentation is summarized,which provides some theoretical references for the follow-up discussion.

关 键 词：实时语义分割 深度学习 计算机视觉 实时预测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]