{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:59:13Z","timestamp":1773615553416,"version":"3.50.1"},"reference-count":25,"publisher":"Allerton Press","issue":"5","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Aut. Control Comp. Sci."],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.3103\/s0146411624700640","type":"journal-article","created":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T12:02:28Z","timestamp":1730894548000},"page":"530-543","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Insulator Defect Detection of Lightweight Rotating YOLOv5 Based on Adaptive Feature Fusion"],"prefix":"10.3103","volume":"58","author":[{"family":"Jiang Xiang Ju","sequence":"first","affiliation":[]},{"family":"Wang Rui Tong","sequence":"additional","affiliation":[]}],"member":"1627","published-online":{"date-parts":[[2024,11,6]]},"reference":[{"key":"7724_CR1","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.3390\/en10071045","volume":"10","author":"Yu. Lv","year":"2017","unstructured":"Lv, Yu., Zhao, W., Li, J., and Zhang, Ya., Simulation of contamination deposition on typical shed porcelain insulators, Energies, 2017, vol. 10, no. 7, p. 1045. https:\/\/doi.org\/10.3390\/en10071045","journal-title":"Energies"},{"key":"7724_CR2","first-page":"1","volume":"36","author":"Z.B. Zhao","year":"2020","unstructured":"Zhao, Z.B., Zhang, W., and Ji, Zh.Y., Concept, research status and prospect of electric power vision technology, Electr. Power Sci. Eng., 2020, vol. 36, no. 1, pp. 1\u20138.","journal-title":"Electr. Power Sci. Eng."},{"key":"7724_CR3","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.1016\/j.jenvman.2017.09.036","volume":"206","author":"R. Bhola","year":"2018","unstructured":"Bhola, R., Krishna, N.H., Ramesh, K.N., Senthilnath, J., and Anand, G., Detection of the power lines in UAV remote sensed images using spectral-spatial methods, J. Environ. Manage., 2018, vol. 206, pp. 1233\u20131242. https:\/\/doi.org\/10.1016\/j.jenvman.2017.09.036","journal-title":"J. Environ. Manage."},{"key":"7724_CR4","doi-asserted-by":"publisher","first-page":"48572","DOI":"10.1109\/access.2019.2909530","volume":"7","author":"H. Shakhatreh","year":"2019","unstructured":"Shakhatreh, H., Sawalmeh, A.H., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., Othman, N.Sh., Khreishah, A., and Guizani, M., Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges, IEEE Access, 2019, vol. 7, pp. 48572\u201348634. https:\/\/doi.org\/10.1109\/access.2019.2909530","journal-title":"IEEE Access"},{"key":"7724_CR5","first-page":"198","volume":"1","author":"Y. Liu","year":"2020","unstructured":"Liu, Y., Lu, Y.P., and Gao, S., Edge detection on infrared image of high voltage porcelain disc type suspension insulator strings, Insul. \n               Surge Arresters, 2020, vol. 1, pp. 198\u2013203.","journal-title":"Surge Arresters"},{"key":"7724_CR6","first-page":"142","volume":"1","author":"X.T. Yao","year":"2020","unstructured":"Yao, X.T., Liu, L., and Li, Z.Y., Identification method of catenary insulator based on Canny edge feature point, Insul. \n               Surge Arrester, 2020, vol. 1, pp. 142\u2013148.","journal-title":"Surge Arrester"},{"key":"7724_CR7","first-page":"2493","volume":"44","author":"X.B. Huang","year":"2018","unstructured":"Huang, X.B., Zhang, H.Y., and Zhang, Y., Composite insulator images segmentation technology based on improved color difference, High Voltage Eng., 2018, vol. 44, no. 8, pp. 2493\u20132500.","journal-title":"High Voltage Eng."},{"key":"7724_CR8","doi-asserted-by":"publisher","first-page":"59022","DOI":"10.1109\/access.2019.2914766","volume":"7","author":"Ye. Zhang","year":"2019","unstructured":"Zhang, Ye., Huang, X., Jia, J., and Liu, X., A recognition technology of transmission lines conductor break and surface damage based on aerial image, IEEE Access, 2019, vol. 7, pp. 59022\u201359036. https:\/\/doi.org\/10.1109\/access.2019.2914766","journal-title":"IEEE Access"},{"key":"7724_CR9","doi-asserted-by":"publisher","first-page":"3584","DOI":"10.13336\/j.1003-6520.hve.20220273","volume":"49","author":"K.P. Liu","year":"2023","unstructured":"Liu, K.P., Li, B.Q., and Qin, L., Review of application research of deep learning object detection algorithms in insulator defect detection of overhead transmission lines, High Voltage Eng., 2023, vol. 49, no. 9, pp. 3584\u20133595. https:\/\/doi.org\/10.13336\/j.1003-6520.hve.20220273","journal-title":"High Voltage Eng."},{"key":"7724_CR10","first-page":"454","volume":"47","author":"P. Luo","year":"2021","unstructured":"Luo, P., Wang, B., and Ma, H.R., Defect recognition method with low false negative rate based on combined target detection framework, High Voltage Eng., 2021, vol. 47, no. 2, pp. 454\u2013464.","journal-title":"High Voltage Eng."},{"key":"7724_CR11","first-page":"2905","volume":"48","author":"B. Li","year":"2022","unstructured":"Li, B., Zeng, J.T., and Zhu, X.S., Detection network for insulator defects based on multi-scale context awareness, High Voltage Eng., 2022, vol. 48, no. 8, pp. 2905\u20132914.","journal-title":"High Voltage Eng."},{"key":"7724_CR12","doi-asserted-by":"publisher","first-page":"5003810","DOI":"10.1109\/tim.2020.3038008","volume":"70","author":"D. Zhang","year":"2021","unstructured":"Zhang, D., Gao, Sh., Yu, L., Kang, G., Wei, X., and Zhan, D., DefGAN: Defect detection GANs with latent space pitting for high-speed railway insulator, IEEE Trans. Instrum. Meas., 2021, vol. 70, p. 5003810. https:\/\/doi.org\/10.1109\/tim.2020.3038008","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"7724_CR13","first-page":"3819","volume":"47","author":"Y. Zhou","year":"2021","unstructured":"Zhou, Y., Xu, B., and Song, A.G., Anomaly location and discrimination method of insulator string based on improved text detection and recognition, High Voltage Eng., 2021, vol. 47, no. 11, pp. 3819\u20133826.","journal-title":"High Voltage Eng."},{"key":"7724_CR14","first-page":"1057","volume":"44","author":"Z.Y. Liu","year":"2020","unstructured":"Liu, Z.Y., Liao, X.R., and Chen, J., Review of visible image intelligent processing for transmission line inspection, Power Syst. Technol., 2020, vol. 44, no. 3, pp. 1057\u20131069.","journal-title":"Power Syst. Technol."},{"key":"7724_CR15","first-page":"1429","volume":"43","author":"H.J. Liu","year":"2021","unstructured":"Liu, H.J., Wang, M., and Liu, L.H., A survey of small object detection based on deep learning, Comput. Eng. Sci., 2021, vol. 43, no. 8, pp. 1429\u20131442.","journal-title":"Comput. Eng. Sci."},{"key":"7724_CR16","doi-asserted-by":"publisher","unstructured":"Dai, J., Qi, H., Xiong, Yu., Li, Yi., Zhang, G., Hu, H., and Wei, Yi., Deformable convolutional networks, 2017 IEEE Int. Conf. on Computer Vision (ICCV), Venice, 2017, IEEE, 2017, pp. 764\u2013773. https:\/\/doi.org\/10.1109\/iccv.2017.89","DOI":"10.1109\/iccv.2017.89"},{"key":"7724_CR17","first-page":"2905","volume":"48","author":"W.P. Li","year":"2022","unstructured":"Li, W.P., Mao, Y.K., and Liao, X., Intelligent diagnosis method of infrared image for substation equipment voltage type thermal defects based on rotating target detection, High Voltage Eng., 2022, vol. 48, no. 8, pp. 2905\u20132914.","journal-title":"High Voltage Eng."},{"key":"7724_CR18","doi-asserted-by":"publisher","unstructured":"Han, K., Wang, Yu., Tian, Q., Guo, J., Xu, Ch., and Xu, Ch., GhostNet: More features from cheap operations, 2020 IEEE\/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Seattle, Wash., 2020, IEEE, 2020, pp. 1577\u20131586. https:\/\/doi.org\/10.1109\/cvpr42600.2020.00165","DOI":"10.1109\/cvpr42600.2020.00165"},{"key":"7724_CR19","doi-asserted-by":"publisher","unstructured":"Lin, T.-Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., and Belongie, S., Feature pyramid networks for object detection, 2017 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Honolulu, Hawaii, 2017, IEEE, 2017, pp. 936\u2013944. https:\/\/doi.org\/10.1109\/cvpr.2017.106","DOI":"10.1109\/cvpr.2017.106"},{"key":"7724_CR20","doi-asserted-by":"publisher","unstructured":"Liu, Sh., Qi, L., Qin, H., Shi, J., and Jia, J., Path aggregation network for instance segmentation, 2018 IEEE\/CVF Conf. on Computer Vision and Pattern Recognition, Salt Lake City, Utah, 2018, IEEE, 2018, pp. 8759\u20138768. https:\/\/doi.org\/10.1109\/cvpr.2018.00913","DOI":"10.1109\/cvpr.2018.00913"},{"key":"7724_CR21","doi-asserted-by":"publisher","unstructured":"Wang, J., Chen, K., Xu, R., Liu, Z., Loy, Ch.Ch., and Lin, D., CARAFE: Content-aware reassembly of features, 2019 IEEE\/CVF Int. Conf. on Computer Vision (ICCV), Seoul, 2019, IEEE, 2019, pp. 3007\u20133016. https:\/\/doi.org\/10.1109\/iccv.2019.00310","DOI":"10.1109\/iccv.2019.00310"},{"key":"7724_CR22","doi-asserted-by":"publisher","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., and Hu, Q., ECA-Net: Efficient channel attention for deep convolutional neural networks, 2020 IEEE\/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Seattle, Wash., 2020, IEEE, 2020, pp. 11531\u201311539. https:\/\/doi.org\/10.1109\/cvpr42600.2020.01155","DOI":"10.1109\/cvpr42600.2020.01155"},{"key":"7724_CR23","first-page":"64","volume":"57","author":"Zh. Chenjia","year":"2021","unstructured":"Chenjia, Zh., Lei, Zh., and Lu, Y., Review of attention mechanism in convolutional neural networks, Comput. Eng. Sci., 2021, vol. 57, no. 20, pp. 64\u201372.","journal-title":"Comput. Eng. Sci."},{"key":"7724_CR24","doi-asserted-by":"publisher","unstructured":"Yang, X. and Yan, J., Arbitrary-oriented object detection with circular smooth label, Computer Vision\u2013ECCV 2020, Vedaldi, A., Bischof, H., Brox, T., and Frahm, J.M., Eds., Lecture Notes in Computer Science, vol.\u00a012353, Cham: Springer, 2020, pp. 677\u2013694. https:\/\/doi.org\/10.1007\/978-3-030-58598-3_40","DOI":"10.1007\/978-3-030-58598-3_40"},{"key":"7724_CR25","doi-asserted-by":"publisher","unstructured":"Zheng, Zh., Wang, P., Liu, W., Li, J., Ye, R., and Ren, D., Distance-IoU loss: Faster and better learning for bounding box regression, Proc. AAAI Conf. Artif. Intell., 2020, vol. 34, no. 7, pp. 12993\u201313000. https:\/\/doi.org\/10.1609\/aaai.v34i07.6999","DOI":"10.1609\/aaai.v34i07.6999"}],"container-title":["Automatic Control and Computer Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411624700640.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.3103\/S0146411624700640","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411624700640.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:01:25Z","timestamp":1773612085000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.3103\/S0146411624700640"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":25,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["7724"],"URL":"https:\/\/doi.org\/10.3103\/s0146411624700640","relation":{},"ISSN":["0146-4116","1558-108X"],"issn-type":[{"value":"0146-4116","type":"print"},{"value":"1558-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10]]},"assertion":[{"value":"9 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 March 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors of this work declare that they have no conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"CONFLICT OF INTEREST"}}]}}