[5] Shahalinejad S, Nooshyar M. Segmentation of retinal blood vessels in glaucoma using a comparative study of edge detection methods in medical image processing$$J$$. J. of Clinical and Experimental Ophthalmology, 2021, 12(6): 892.

[7] Markiewicz T, Cichowicz M, Kozowski W. Alternative colour space construction of the stain reaction in FISH image analysis for quantification of the HER2 gene amplification$$J$$. Przeglad Elektrotechniczny, 2012, 88(3A): 10-12.

[8] Shirley J W, Ty S, Takebayashi S, et al. FISH Finder: A high-throughput tool for analyzing FISH images$$J$$. Bioinformatics, 2011, 27(7): 933-938.

[11] Jin H S, Cho H, Huang J F, et al. Hovering control of UUV through underwater object detection based on deep learning$$J$$. Ocean Engineering, 2022, 253: 111321.

[12] Zhang N, Donahue J, Girshick R, et al. Part-based R-CNNs for fine-grained category detection$$C$$// Computer Vision-ECCV 2014: the 13th European Conf., Zurich, Switzerland, September 6-12, 2014, Proc., Part Ⅰ 13. Springer International Publishing, 2014: 834-849.

[13] Girshick R. Fast R-CNN$$C$$// Proc. of the IEEE Inter. Conf. on Computer Vision, 2015: 1440-1448.

[14] Ren S, He K, Girshick R, et al. Faster R-CNN: Towards real-time object detection with region proposal networks$$J$$. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1149.

[16] Hu W, Xiong J, Liang J, et al. A method of citrus epidermis defects detection based on an improved YOLOv5$$J$$. Biosystems Engineering, 2023, 227: 19-35.

[17] Redmon J, Divvala S, Girshick R, et al. You only look once: Unified, real-time object detection$$C$$// Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, 2016: 779-788.