SIA OpenIR  > 工业控制网络与系统研究室
Analysis on the Impact of Data Augmentation on Target Recognition for UAV-Based Transmission Line Inspection
Song CH(宋纯贺)1,2,3,4; Xu WX(徐文想)1,2,3,4,5; Wang ZF(王忠锋)1,2,3,4; Yu SM(于诗矛)1,2,3,4; Zeng P(曾鹏)1,2,3,4
Department工业控制网络与系统研究室
Source PublicationComplexity
ISSN1076-2787
2020
Volume2020Pages:1-11
Indexed BySCI ; EI
EI Accession number20204409412112
WOS IDWOS:000581693300013
Contribution Rank1
Funding OrganizationNational Key R&D Program of China under Grant 2018YFB1700200 ; National Nature Science Foundation of China under Grant U1908212 ; State Grid Corporation Science and Technology Project (SG2NK00DWJS1800123) ; State Grid Shanghai Electric Power Corporation's 2020 technology project “Research on Automatic Networking and Data Fusion Technology of Power IoT Sensors” (52090F1900BK).
Abstract

Target recognition is one of the core tasks of transmission line inspection based on Unmanned Aerial Vehicle (UAV), and at present plenty of deep learning-based methods have been developed for it. To enhance the generalization ability of the recognition models, a huge number of training samples are needed to cover most of all possible situations. However, due to the complexity of the environmental conditions and targets, and the limitations of images' collection and annotation, the samples usually are insufficient when training a deep learning model for target recognition, which is one of the main factors reducing the performance of the model. To overcome this issue, some data augmentation methods have been developed to generate additional samples for model training. Although these methods have been widely used, currently there is no quantitative study on the impact of the data augmentation methods on target recognition. In this paper, taking insulator strings as the target, the impact of a series of widely used data augmentation methods on the accuracy of target recognition is studied, including histogram equalization, Gaussian blur, random translation, scaling, cutout, and rotation. Extensive tests are carried out to verify the impact of the augmented samples in the training set, the test set, or the both. Experimental results show that data augmentation plays an important role in improving the accuracy of recognition models, in which the impacts of the data augmentation methods such as Gaussian blur, scaling, and rotation are significant.

Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/27840
Collection工业控制网络与系统研究室
Corresponding AuthorZeng P(曾鹏)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China
3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
4.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
5.University of Chinese Academy of Sciences, Beijing 100049, China
6.School of Computing, University of Portsmouth, Portsmouth, United Kingdom
Recommended Citation
GB/T 7714
Song CH,Xu WX,Wang ZF,et al. Analysis on the Impact of Data Augmentation on Target Recognition for UAV-Based Transmission Line Inspection[J]. Complexity,2020,2020:1-11.
APA Song CH,Xu WX,Wang ZF,Yu SM,&Zeng P.(2020).Analysis on the Impact of Data Augmentation on Target Recognition for UAV-Based Transmission Line Inspection.Complexity,2020,1-11.
MLA Song CH,et al."Analysis on the Impact of Data Augmentation on Target Recognition for UAV-Based Transmission Line Inspection".Complexity 2020(2020):1-11.
Files in This Item:
File Name/Size DocType Version Access License
Analysis on the Impa(8530KB)期刊论文出版稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Song CH(宋纯贺)]'s Articles
[Xu WX(徐文想)]'s Articles
[Wang ZF(王忠锋)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Song CH(宋纯贺)]'s Articles
[Xu WX(徐文想)]'s Articles
[Wang ZF(王忠锋)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Song CH(宋纯贺)]'s Articles
[Xu WX(徐文想)]'s Articles
[Wang ZF(王忠锋)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Analysis on the Impact of Data Augmentation on Target Recognition for UAV-Based Transmission Line Inspection.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.