{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T19:07:15Z","timestamp":1754161635490,"version":"3.41.2"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3592017","type":"journal-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T18:44:30Z","timestamp":1753296270000},"page":"130430-130445","source":"Crossref","is-referenced-by-count":0,"title":["Power Equipment Image Recognition Method Based on Feature Extraction and Deep Learning"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9831-5037","authenticated-orcid":false,"given":"Shuang","family":"Lin","sequence":"first","affiliation":[{"name":"State Grid Fujian Electric Power Research Institute, Fuzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"4","key":"ref1","first-page":"1041","article-title":"Research and application of big data analysis of power equipment condition","volume":"44","author":"Jiang","year":"2018","journal-title":"High Voltage Eng."},{"issue":"8","key":"ref2","first-page":"2548","article-title":"Precise positioning technology of wild fire nearby transmission lines by visible and infrared vision","volume":"44","author":"He","year":"2018","journal-title":"High Voltage Eng."},{"issue":"10","key":"ref3","first-page":"161","article-title":"ED-YOLO power inspection UAV obstacle avoidance target detection algorithm based on model compression","volume":"42","author":"Peng","year":"2021","journal-title":"Chin. J. Sci. Instrum."},{"issue":"1","key":"ref4","first-page":"207","article-title":"Power target detection in aerial images based on SSD deep neural network","volume":"37","author":"Shi","year":"2022","journal-title":"J. Data Acquisition Process."},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2024.3481543"},{"issue":"36","key":"ref6","first-page":"134","article-title":"Application of particle swarm fused KFCM and classification model of SVM for fault diagnosis of circuit breaker","volume":"33","author":"Mei","year":"2013","journal-title":"Proc. CSEE"},{"issue":"9","key":"ref7","first-page":"2985","article-title":"Research and application of data-driven artificial intelligence technology for condition analysis of power equipment","volume":"46","author":"Tang","year":"2020","journal-title":"High Voltage Eng."},{"issue":"5","key":"ref8","first-page":"81","article-title":"Application of remote digital video monitoring and image recognition technology in power system","volume":"29","author":"Sun","year":"2005","journal-title":"Power Syst. Technol."},{"issue":"11","key":"ref9","first-page":"3561","article-title":"Pollution status detection of insulators in contact net based on UV imaging","volume":"41","author":"Jin","year":"2015","journal-title":"High Voltage Eng."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CISP.2012.6469854"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.13336\/j.1003-6520.hve.20170303028"},{"issue":"11","key":"ref12","first-page":"120","article-title":"Power equipment image recognition method based on joint sparse representation of multiple features","volume":"39","author":"Qiao","year":"2020","journal-title":"Techn. Autom. Appl."},{"issue":"6","key":"ref13","first-page":"1329","article-title":"Application of an improved algorithm based on watershed combined with Krawtchouk invariant moment in inspection image processing of substations","volume":"35","author":"Cui","year":"2015","journal-title":"Proc. CSEE"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/s13640-019-0452-5"},{"issue":"6","key":"ref15","first-page":"1865","article-title":"Overview of application of deep learning with image data and spatio-temporal data of power grid","volume":"43","author":"Zhang","year":"2019","journal-title":"Power Syst. Technol."},{"issue":"1","key":"ref16","first-page":"2","article-title":"Review on application of artificial intelligence in power system and integrated energy system","volume":"43","author":"Yang","year":"2019","journal-title":"Automat. Electr. Power Syst."},{"issue":"23","key":"ref17","first-page":"9491","article-title":"Electrical equipment image classification based on deep learning network","volume":"20","author":"Wang","year":"2020","journal-title":"Sci. Technol. Eng."},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1732\/1\/012025"},{"issue":"8","key":"ref19","first-page":"1687","article-title":"Image recognition of power equipment based on texture parameters and GA-BP neutral network","volume":"49","author":"Liu","year":"2021","journal-title":"Comput. Digit. Eng."},{"issue":"9","key":"ref20","first-page":"129","article-title":"Image recognition of electric equipment based on GoogLeNet Inception-V3 model","volume":"56","author":"Xu","year":"2020","journal-title":"High Voltage Apparatus"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2022.3150110"},{"issue":"S1","key":"ref22","first-page":"1","article-title":"Review of attention mechanism","volume":"41","author":"Ren","year":"2021","journal-title":"J. Comput. Appl."},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-022-0271-y"},{"key":"ref24","first-page":"2204","article-title":"Recurrent models of visual attention","volume-title":"Proc. 27th Int. Conf. Neural Inf. Process. Syst.","author":"Mnih"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1049\/hve2.12472"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2025.3552628"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.170"},{"issue":"2","key":"ref32","first-page":"275","article-title":"Attention-aware and semantic-aware network for RGB-D indoor semantic segmentation","volume":"44","author":"Duan","year":"2021","journal-title":"Chin. J. Comput."},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref34","first-page":"1","article-title":"An image is worth 16\u00d716 words-transformers for image recognition at scale","volume-title":"Proc. 9th Int. Conf. Learn. Represent.","author":"Dosovitskiy"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00009"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11091302.pdf?arnumber=11091302","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T05:01:43Z","timestamp":1753765303000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11091302\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3592017","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2025]]}}}