{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T18:26:36Z","timestamp":1781029596863,"version":"3.54.1"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62203197"],"award-info":[{"award-number":["62203197"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Liaoning Doctoral Research Start-Up Fund","award":["2022-bs-330"],"award-info":[{"award-number":["2022-bs-330"]}]},{"name":"University-Level Research Project: Doctoral Start-Up Fund","award":["21-1036"],"award-info":[{"award-number":["21-1036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3363430","type":"journal-article","created":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T18:52:21Z","timestamp":1707331941000},"page":"22649-22661","source":"Crossref","is-referenced-by-count":9,"title":["HRD-YOLOX Based Insulator Identification and Defect Detection Method for Transmission Lines"],"prefix":"10.1109","volume":"12","author":[{"given":"Ying","family":"Li","sequence":"first","affiliation":[{"name":"School of Electrical and Control Engineering, Liaoning Technical University, Fuxin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7482-8871","authenticated-orcid":false,"given":"Dongdong","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Electrical and Control Engineering, Liaoning Technical University, Fuxin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Control Engineering, Liaoning Technical University, Fuxin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanjie","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electrical and Control Engineering, Liaoning Technical University, Fuxin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8121467"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICMTMA.2018.00035"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/WPTC51349.2021.9458215"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.4236\/epe.2013.54B219"},{"issue":"1","key":"ref5","first-page":"10","article-title":"Intelligent monitoring system for hazards of transmission line based on deep learning","volume":"17","author":"Chenqi","year":"2018","journal-title":"J. Nantong Univ. (Natural Sci. Ed.)"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1142\/9789814733878_0046"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-16-7466-2_115"},{"key":"ref8","volume-title":"Transmission Line Inspection Using Suspended Robot: Cost Effective Analysis and Operational Routing Identification","author":"Nagarajan","year":"2018"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.23919\/ChiCC.2019.8865560"},{"key":"ref10","first-page":"34","article-title":"Bibliometric analysis of one-stage and two-stage object detection","volume":"4910","author":"Lohia","year":"2021","journal-title":"Library Philosophy Pract."},{"issue":"65","key":"ref11","first-page":"65","article-title":"Deep learning-based transmission line anti-vibration Hammer fault detection","volume":"11","author":"Feng","year":"2020","journal-title":"Auto. Ins."},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.17775\/CSEEJPES.2019.00460"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.2174\/2352096514666211026143543"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.23919\/ChiCC.2019.8866322"},{"key":"ref15","article-title":"Exceptional capacitive deionization desalination performance of hollow bowl-like carbon derived from MOFs in brackish water","volume":"278","author":"Xue","year":"2021","journal-title":"Separat. Purification Technol."},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-7605-3_66"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/su14106066"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICOTEN52080.2021.9493477"},{"key":"ref20","article-title":"YOLOX: Exceeding YOLO series in 2021","author":"Ge","year":"2021","journal-title":"arXiv:2107.08430"},{"key":"ref21","first-page":"13","article-title":"Resurrecting the sigmoid in deep learning through dynamical isometry: Theory and practice","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Pennington"},{"key":"ref22","article-title":"Towards explaining deep learning: Asymptotic properties of ReLU FFN sieve estimators","author":"Fallahgoul","year":"2019","journal-title":"Social Sci. Electron. Publishing"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2389824"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00125"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00579"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00089"},{"issue":"2","key":"ref29","first-page":"267","article-title":"Remote sensing image target detection based on two-way feature fusion and feature selection","volume":"50","author":"Jinsheng","year":"2022","journal-title":"J. Electr."},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.107836"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2759509"},{"key":"ref33","first-page":"11","article-title":"DropBlock: A regularization method for convolutional networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Ghiasi"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref36","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12363"},{"key":"ref38","article-title":"Slim-neck by GSConv: A better design paradigm of detector architectures for autonomous vehicles","author":"Li","year":"2022","journal-title":"arXiv:2206.02424"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10423764.pdf?arnumber=10423764","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T19:00:31Z","timestamp":1709924431000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10423764\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3363430","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}