[1] Meng J R. Aero-engine interior damage recognition based on support vector machine[J]. Journal of Heilongjiang Institute of Science and Technology, 19, 50-53(2009).

[2] Ma C, Wang Y N, Wu Y G et al. Hard object impact damage characteristics of aero engine fan blade[J]. Journal of Aerospace Power, 32, 1105-1111(2017).

[3] Zheng L, Luo Z M, Zhang B. The application and development of non-destructive testing in aircraft engine maintenance[J]. Modern Manufacturing Technology and Equipment, 62-63(2014).

[4] He J H, Zhang D S, Zhao C et al. Detection technology and application analysis of aero-engine blade crack[J]. Internal Combustion Engine＆Parts, 151-152(2020).

[5] Qiu T H, Wang L, Wang P et al. Research on object detection algorithm based on improved YOLOv5[J]. Computer Engineering and Applications, 58, 63-73(2022).

[6] Girshick R, Donahue J, Darrell T et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C], 580-587(2014).

[7] Girshick R. Fast R-CNN[C], 1440-1448(2015).

[8] 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).

[9] Liu W, Anguelov D, Erhan D et al. SSD: single shot MultiBox detector[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9905, 21-37(2016).

[10] Xiang K, Li S S, Luan M H et al. Aluminum product surface defect detection method based on improved Faster RCNN[J]. Chinese Journal of Scientific Instrument, 42, 191-198(2021).

[11] Lai W H, Zhou M R, Hu F et al. Coal gangue detection based on multi-spectral imaging and improved YOLO v4[J]. Acta Optica Sinica, 40, 2411001(2020).

[12] Cheng S, Yang H G, Xu X Q et al. Improved lightweight X-ray aluminum alloy weld defect detection algorithm based on YOLOv5[J]. Chinese Journal of Lasers, 49, 2104005(2022).

[13] Sun Y C, Pan S G, Zhao T et al. Traffic light detection based on optimized YOLOv3 algorithm[J]. Acta Optica Sinica, 40, 1215001(2020).

[14] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection[C], 779-788(2016).

[15] Redmon J, Farhadi A. YOLO9000: better, faster, stronger[C], 6517-6525(2017).

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

[17] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

[18] Wang C Y, Mark Liao H Y, Wu Y H et al. CSPNet: a new backbone that can enhance learning capability of CNN[C], 1571-1580(2020).

[19] He K M, Zhang X Y, Ren S Q et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1904-1916(2015).

[20] Liu S, Qi L, Qin H F et al. Path aggregation network for instance segmentation[C], 8759-8768(2018).

[21] Zhu X H, Qian L P, Fu W. Overview of research on image data enhancement technology[J]. Software Guide, 20, 230-236(2021).

[22] Wang L M, Duan J, Xin L W. YOLOv5 helmet wear detection method with introduction of attention mechanism[J]. Computer Engineering and Applications, 58, 303-312(2022).

[23] Hou Q B, Zhou D Q, Feng J S. Coordinate attention for efficient mobile network design[C], 13708-13717(2021).

[24] Song T, Li Y, Wang J. Improved YOLOv5s vehicle infrared image target detection[J]. Modern Computer, 28, 21-28(2022).

[25] Zheng Z H, Wang P, Ren D W et al. Enhancing geometric factors in model learning and inference for object detection and instance segmentation[J]. IEEE Transactions on Cybernetics, 52, 8574-8586(2022).

[26] Zhang Y F, Ren W, Zhang Z et al. Focal and efficient IOU loss for accurate bounding box regression[J]. Neurocomputing, 506, 146-157(2022).