基于深度学习的图像语义分割研究综述

Jinliang Ou, Hong Lin, Z. Qiang, Zhuqun Chen
{"title":"基于深度学习的图像语义分割研究综述","authors":"Jinliang Ou, Hong Lin, Z. Qiang, Zhuqun Chen","doi":"10.1109/CCIS57298.2022.10016328","DOIUrl":null,"url":null,"abstract":"In recent years, inspired by deep learning, the performance of semantic segmentation has been greatly improved. According to the research status of semantic segmentation based on deep learning, this paper firstly combs the semantic segmentation method based on convolutional neural network and the new method based on Transformer respectively, and briefly introduces their core algorithms. Then, the performance of these methods on different datasets is compared and analyzed. Finally, the semantic segmentation methods and the future development trend are summarized.","PeriodicalId":374660,"journal":{"name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Survey of images semantic segmentation based on deep learning\",\"authors\":\"Jinliang Ou, Hong Lin, Z. Qiang, Zhuqun Chen\",\"doi\":\"10.1109/CCIS57298.2022.10016328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, inspired by deep learning, the performance of semantic segmentation has been greatly improved. According to the research status of semantic segmentation based on deep learning, this paper firstly combs the semantic segmentation method based on convolutional neural network and the new method based on Transformer respectively, and briefly introduces their core algorithms. Then, the performance of these methods on different datasets is compared and analyzed. Finally, the semantic segmentation methods and the future development trend are summarized.\",\"PeriodicalId\":374660,\"journal\":{\"name\":\"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCIS57298.2022.10016328\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIS57298.2022.10016328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

近年来,在深度学习的启发下,语义分割的性能有了很大的提高。根据基于深度学习的语义分割的研究现状,本文首先对基于卷积神经网络的语义分割方法和基于Transformer的语义分割新方法进行了梳理,并简要介绍了它们的核心算法。然后,比较分析了这些方法在不同数据集上的性能。最后,对语义分割的方法和未来的发展趋势进行了总结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Survey of images semantic segmentation based on deep learning
In recent years, inspired by deep learning, the performance of semantic segmentation has been greatly improved. According to the research status of semantic segmentation based on deep learning, this paper firstly combs the semantic segmentation method based on convolutional neural network and the new method based on Transformer respectively, and briefly introduces their core algorithms. Then, the performance of these methods on different datasets is compared and analyzed. Finally, the semantic segmentation methods and the future development trend are summarized.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信