[1] Wan K, Jing Q. Communication, integration and progress—looking at the future of oral comfort in China from the current situation of dental sedation and analgesia in the United States and Japan[J]. Chinese Journal of Stomatologial Continuing Education, 31-37(2021).

[2] Hinton G E, Salakhutdinov R R. Reducing the dimensionality of data with neural networks[J]. Science, 313, 504-507(2006).

[3] LeCun Y, Bottou L, Bengio Y et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 86, 2278-2324(1998).

[4] Manjula K, Devi G D, Vijayarekha K. Detection of dental diseases using classification algorithms[J]. International Journal of Recent Technology and Engineering, 8, 4485-4489(2019).

[5] Lee J H, Kim D H, Jeong S N et al. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm[J]. Journal of Dentistry, 77, 106-111(2018).

[6] Szegedy C, Vanhoucke V, Ioffe S et al. Rethinking the inception architecture for computer vision[C], 2818-2826(2016).

[7] Lee J H, Kim D H, Jeong S N et al. Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm[J]. Journal of Periodontal & Implant Science, 48, 114-123(2018).

[8] Shu L, Zhang Z J, Lei B. Research on Dense-Yolov5 algorithm for infrared target detection[J]. Optics & Optoelectronic Technology, 19, 69-75(2021).

[9] Krois J, Ekert T, Meinhold L et al. Deep learning for the radiographic detection of periodontal bone loss[J]. Scientific Reports, 9, 8495(2019).

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

[11] Liu W, Anguelov D, Erhan D et al[EB/OL]. SSD: single shot MultiBox detector. https://arxiv.org/abs/1512.02325

[12] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. Navab N, Hornegger J, Wells W M, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science, 9351, 234-241(2015).

[13] Chen H, Zhang K L, Lü P J et al. A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films[J]. Scientific Reports, 9, 3840(2019).

[14] 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).

[15] Zhang X, Liang Y, Li W et al. Development and evaluation of deep learning for screening dental caries from oral photographs[J]. Oral Diseases, 28, 173-181(2022).

[16] Khan H A, Haider M A, Ansari H A et al. Automated feature detection in dental periapical radiographs by using deep learning[J]. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology, 131, 711-720(2021).

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

[18] Hou G F, Fang F Z. Study on detection of diabetes fundus disease based on deep learning[J/OL]. Laser & Optoelectronics Progress, 1-12. http://kns.cnki.net/kcms/detail/31.1690.TN.20211215.1119.008.html

[19] Mohiyuddin A, Basharat A, Ghani U et al. Breast tumor detection and classification in mammogram images using modified YOLOv5 network[J]. Computational and Mathematical Methods in Medicine, 2022, 1359019(2022).

[20] Yao J, Qi J M, Zhang J et al. A real-time detection algorithm for kiwifruit defects based on YOLOv5[J]. Electronics, 10, 1711(2021).

[21] An Q Z, Pan Z X, Liu L et al. DRBox-v2: an improved detector with rotatable boxes for target detection in SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 8333-8349(2019).

[22] Gao M T, Sun H, Tang Y Q et al. Fingerprint second-order minutiae detection method based on improved YOLOv5[J/OL]. 激光与光电子学进展, 1-19. http://kns.cnki.net/kcms/detail/31.1690.tn.20220317.1011.002.html

[23] Wan J J, Chen B L, Yu Y T. Polyp detection from colorectum images by using attentive YOLOv5[J]. Diagnostics, 11, 2264(2021).