Semantic Segmentation of Substation Scenes Using Attention-Based Model

Qian Chen, Chang-Hua Zhang, Hao Li, Naijia Wan, Donghui Wang, Bin Xu
{"title":"Semantic Segmentation of Substation Scenes Using Attention-Based Model","authors":"Qian Chen, Chang-Hua Zhang, Hao Li, Naijia Wan, Donghui Wang, Bin Xu","doi":"10.1109/ICET51757.2021.9451012","DOIUrl":null,"url":null,"abstract":"Inspection robots are widely used in transformer substation for inspection tasks. In order to complete the task, the robots need to understand and recognize road scenes. However, the transformer substation contains lots of similar and small equipment, which are difficult to recognize. To address this problem, we propose a semantic segmentation model to recognize road scenes. Specifically, our proposed model discriminates the equipment by leveraging multi-view method. We use attention mechanism to strengthen the relationship between pixels that belong to an individual category. Compared with previous methods, our approach achieves a good performance in a new dataset from a transformer substation and shows robustness in recognizing equipment of transformer substation.","PeriodicalId":316980,"journal":{"name":"2021 IEEE 4th International Conference on Electronics Technology (ICET)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Electronics Technology (ICET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET51757.2021.9451012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Inspection robots are widely used in transformer substation for inspection tasks. In order to complete the task, the robots need to understand and recognize road scenes. However, the transformer substation contains lots of similar and small equipment, which are difficult to recognize. To address this problem, we propose a semantic segmentation model to recognize road scenes. Specifically, our proposed model discriminates the equipment by leveraging multi-view method. We use attention mechanism to strengthen the relationship between pixels that belong to an individual category. Compared with previous methods, our approach achieves a good performance in a new dataset from a transformer substation and shows robustness in recognizing equipment of transformer substation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于注意力模型的变电站场景语义分割
巡检机器人广泛应用于变电站的巡检任务中。为了完成任务,机器人需要理解和识别道路场景。但是,变电站中存在大量相似的小型设备,难以识别。为了解决这个问题,我们提出了一个语义分割模型来识别道路场景。具体来说,我们提出的模型利用多视图方法来区分设备。我们使用注意机制来加强属于单个类别的像素之间的关系。与以往的方法相比,我们的方法在一个新的变电站数据集上取得了良好的性能,并且在变电站设备识别方面表现出鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
[ICET 2021 Front cover] Fault Diagnosis and Analysis of Analog Module in a Nuclear Power Plant Representational-Interactive Feature Fusion Method for Text Intent Matching Fabrication and Investigation of NiOx MSM Structure on 4H-SiC Substrate Research on Inversion Algorithm of Interferometric Microwave Radiometer Based on PSO-LM-BP Model
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1