{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T23:23:54Z","timestamp":1783034634787,"version":"3.54.6"},"reference-count":30,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T00:00:00Z","timestamp":1674172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Young Talents Project of Scientific Research Foundation of Education Department of Hubei Province","award":["Q20151601"],"award-info":[{"award-number":["Q20151601"]}]},{"name":"Young Talents Project of Scientific Research Foundation of Education Department of Hubei Province","award":["2020YFB0905900"],"award-info":[{"award-number":["2020YFB0905900"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R &amp; D Program of China","doi-asserted-by":"publisher","award":["Q20151601"],"award-info":[{"award-number":["Q20151601"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R &amp; D Program of China","doi-asserted-by":"publisher","award":["2020YFB0905900"],"award-info":[{"award-number":["2020YFB0905900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The accuracy of insulators and their defect identification by UAVs (unmanned aerial vehicles) in transmission-line inspection needs to be further improved, and the model size of the detection algorithm is significantly reduced to make it more suitable for edge-end deployment. In this paper, the algorithm uses a lightweight GhostNet module to reconstruct the backbone feature extraction network of the YOLOv4 model and employs depthwise separable convolution in the feature fusion layer. The model is lighter on the premise of ensuring the effect of image information extraction. Meanwhile, the ECA-Net channel attention mechanism is embedded into the feature extraction layer and PANet (Path Aggregation Network) to improve the recognition accuracy of the model for small targets. The experimental results show that the size of the improved model is reduced from 244 MB to 42 MB, which is only 17.3% of the original model. At the same time, the mAp of the improved model is 0.77% higher than that of the original model, reaching 95.4%. Moreover, the mAP compared with YOLOv5-s and YOLOX-s, respectively, is improved by 1.98% and 1.29%. Finally, the improved model is deployed into Jetson Xavier NX and run at a speed of 8.8 FPS, which is 4.3 FPS faster than the original model.<\/jats:p>","DOI":"10.3390\/s23031216","type":"journal-article","created":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T06:52:41Z","timestamp":1674197561000},"page":"1216","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["A Lightweight Algorithm for Insulator Target Detection and Defect Identification"],"prefix":"10.3390","volume":"23","author":[{"given":"Gujing","family":"Han","sequence":"first","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"},{"name":"State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"},{"name":"State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Li","sequence":"additional","affiliation":[{"name":"State Grid Information & Telecommunication Group Co., Ltd., Beijing 102211, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saidian","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"},{"name":"State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruijie","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"},{"name":"State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiwei","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"},{"name":"State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"He","sequence":"additional","affiliation":[{"name":"School of Electrical and Automation, Wuhan University, Wuhan 430072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiqi","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electrical and Automation, Wuhan University, Wuhan 430072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1471-3872","authenticated-orcid":false,"given":"Liang","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Electrical and Automation, Wuhan University, Wuhan 430072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,20]]},"reference":[{"key":"ref_1","first-page":"155","article-title":"Insulator defect detection based on enhanced feature pyramid and deformable convolution","volume":"40","author":"Zhang","year":"2021","journal-title":"Electr. 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