[1] Liu K P, Li B Q, Qin L et al. Review on the application of deep learning target detection algorithm in insulator defect detection of overhead transmission lines[J]. High Voltage Engineering, 49, 3584-3595(2023).

[2] Huang F Z, Wang T C. Insulator defect detection based on lightweight GCP-YOLOv8s[J]. Laser & Optoelectronics Progress, 62, 0212004(2025).

[3] Shan H L, Wang S Y, Tong J Y et al. Multi-scale optical remote sensing image target detection based on enhanced small target features[J]. Acta Optica Sinica, 44, 0628006(2024).

[4] Martinez C, Sampedro C, Chauhan A et al. Towards autonomous detection and tracking of electric towers for aerial power line inspection[C], 284-295(2014).

[5] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

[6] Zhai Y J, Wang L Y, Guo C B. Insulator object detection in complex background based on Faster R-CNN[J]. Electronic Measurement Technology, 46, 187-194(2023).

[7] Sun Z F, Yu J H, Zhu X F et al. Dental-disease-recognition algorithm of panoramic oral radiograph based on improved YOLOv5s[J]. Chinese Journal of Lasers, 51, 1507106(2024).

[8] Li R H, Yang Y, Li N et al. Transmission line pin detection based on improved SSD[C](2022).

[9] Jia X F, Wu X R, Zhao B T. Lightweight detection network for insulator self-detonation defect DE-YOLO[J]. Journal of Electronic Measurement and Instrumentation, 37, 28-35(2023).

[10] Guo Y, Ma M L, Li D L. Detection of surface defects in lightweight insulators using improved YOLOv5[J]. Laser & Optoelectronics Progress, 60, 2412007(2023).

[11] Zhai Y J, Zhao X Y, Wang L Y et al. IDD-YOLOv7: a lightweight method for multiple defect detection of insulators in transmission lines[J]. Journal of Graphics, 45, 90-101(2024).

[12] Hu D A, Yu M, Wu X Y et al. DGW-YOLOv8: a small insulator target detection algorithm based on deformable attention backbone and WIoU loss function[J]. IET Image Processing, 18, 1096-1108(2024).

[13] Wang A, Chen H, Lin Z J et al. RepViT: revisiting mobile CNN from ViT perspective[C], 15909-15920(2024).

[14] Koonce B[M]. Convolutional neural networks with Swift for TensorFlow: image recognition and dataset categorization(2021).

[15] Ouyang D L, He S, Zhang G Z et al. Efficient multi-scale attention module with cross-spatial learning[C](2023).

[16] Xu S B, Zheng S C, Xu W H et al. HCF-net: hierarchical context fusion network for infrared small object detection[EB/OL]. https://arxiv.org/abs/2403.10778v1

[17] Chen Z X, He Z W, Lu Z M. DEA-net: single image dehazing based on detail-enhanced convolution and content-guided attention[J]. IEEE Transactions on Image Processing, 33, 1002-1015(2024).

[18] Zheng Z H, Wang P, Liu W et al. Distance-IoU loss: faster and better learning for bounding box regression[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12993-13000(2020).

[19] Zhang H, Xu C, Zhang S J. Inner-IoU: more effective intersection over union loss with auxiliary bounding box[EB/OL]. https://arxiv.org/abs/2311.02877v4

[20] Tong Z J, Chen Y H, Xu Z W et al. Wise-IoU: bounding box regression loss with dynamic focusing mechanism[EB/OL]. https://arxiv.org/abs/2301.10051v3

[21] Tao X, Zhang D P, Wang Z H et al. Detection of power line insulator defects using aerial images analyzed with convolutional neural networks[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50, 1486-1498(2020).

[22] Liu Y, Liu D C, Huang X B et al. Insulator defect detection with deep learning: a survey[J]. IET Generation, 17, 3541-3558(2023).

[23] Redmon J, Farhadi A. YOLOv3: an incremental improvement[EB/OL]. https://arxiv.org/abs/1804.02767v1

[24] Liu L, Huang K Y, Bai Y A et al. Real-time detection model of electrical work safety belt based on lightweight improved YOLOv5[J]. Journal of Real-Time Image Processing, 21, 151(2024).

[25] Wang C Y, Bochkovskiy A, Liao H Y M. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[C], 7464-7475(2023).

[26] Kang R H, Huang X H, Huang J J et al. Insulating glove wearing state detection for substation personnel based on faster-YOLOv8[J]. IEEJ Transactions on Electrical and Electronic Engineering, 19, 1369-1376(2024).

[27] Zhao Y A, Lv W Y, Xu S L et al. DETRs beat YOLOs on real-time object detection[C], 16965-16974(2024).

[28] Lyu H T, Qiu F, An L et al. Deer survey from drone thermal imagery using enhanced faster R-CNN based on ResNets and FPN[J]. Ecological Informatics, 79, 102383(2024).

[29] Li D, Yang P F, Zou Y T. Optimizing insulator defect detection with improved DETR models[J]. Mathematics, 12, 1507(2024).

[30] Zhang L, Li B Q, Cui Y et al. Research on improved YOLOv8 algorithm for insulator defect detection[J]. Journal of Real-Time Image Processing, 21, 22(2024).