Righolt AJ, Jevdjevic M, Marcenes W, Listl S. Global-, Regional-, and Country-Level Economic Impacts of Dental Diseases in 2015. J Dent Res, 97(5):501-507, 2018.

Article  CAS  PubMed  Google Scholar 

Nascimento MM, Bader JD, Qvist V, Litaker MS, Williams OD, Rindal DB, et al. Concordance between preoperative and postoperative assessments of primary caries lesion depth: results from the Dental PBRN. Oper Dent, 35(4):389-396, 2010.

Article  PubMed  PubMed Central  Google Scholar 

Menem R, Barngkgei I, Beiruti N, Al Haffar I, Joury E. The diagnostic accuracy of a laser fluorescence device and digital radiography in detecting approximal caries lesions in posterior permanent teeth: an in vivo study. Lasers Med Sci, 32:621-628, 2017.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cantu AG, Gehrung S, Krois J, Chaurasia A, Rossi JG, Gaudin R, et al. Detecting caries lesions of different radiographic extension on bitewings using deep learning. J Dent, 100:103425, 2020.

Article  PubMed  Google Scholar 

Mertens S, Krois J, Cantu AG, Arsiwala LT, Schwendicke F. Artificial intelligence for caries detection: Randomized trial. J Dent, 115:103849, 2021.

Article  PubMed  Google Scholar 

Lee Y. Diagnosis and prevention strategies for dental caries. J Lifestyle Med, 3(2):107, 2013.

PubMed  PubMed Central  Google Scholar 

Redmon J, Divvala S, Girshick R, Farhadi A, editors. You only look once: Unified, real-time object detection. Proceedings of the IEEE conference on computer vision and pattern recognition, 779–788, 2016.

Thanh MTG, Van Toan N, Ngoc VTN, Tra NT, Giap CN, Nguyen DM. Deep Learning Application in Dental Caries Detection Using Intraoral Photos Taken by Smartphones. Appl Sci, 12(11):5504, 2022.

Article  CAS  Google Scholar 

Sonavane A, Kohar R. Dental Cavity Detection Using YOLO. Proceedings of Data Analytics and Management: Springer, 141–152, 2022.

Bayraktar Y, Ayan E. Diagnosis of interproximal caries lesions with deep convolutional neural network in digital bitewing radiographs. Clin Oral Invest, 26(1):623-632, 2022.

Article  Google Scholar 

Pitts NB, Ismail AI, Martignon S, Ekstrand K, Douglas GV, Longbottom C, et al. ICCMS™ guide for practitioners and educators, 2014.

Panyarak W, Suttapak W, Wantanajittikul K, Charuakkra A, Prapayasatok S. Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS™ radiographic scoring system. Clin Oral Invest, 27(4):1731-1742, 2023.

Wang CY, Bochkovskiy A, Liao HYM. YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 7464–7475, 2022.

Zhang Z, He T, Zhang H, Zhang Z, Xie J, Li M. Bag of freebies for training object detection neural networks. arXiv preprint arXiv:1902.04103, 2019.

Hossin M, Sulaiman MN. A review on evaluation metrics for data classification evaluations. Int J Data Min Knowl Manag Process, 5(2):1, 2015.

Article  Google Scholar 

Padilla R, Passos WL, Dias TL, Netto SL, Da Silva EA. A comparative analysis of object detection metrics with a companion open-source toolkit. Electronics, 10(3):279, 2021.

Article  Google Scholar 

Manning CD. Introduction to information retrieval: Syngress Publishing; 2008.

Selvaraju RR, Cogswell M, Das A, Vedantam R, Parikh D, Batra D, editors. Grad-cam: Visual explanations from deep networks via gradient-based localization. Proceedings of the IEEE international conference on computer vision, 618–626, 2017.

Padilla R, Netto SL, Da Silva EA, editors. A survey on performance metrics for object-detection algorithms. 2020 international conference on systems, signals and image processing (IWSSIP). IEEE, 237–242, 2020.

Wang C-Y, Bochkovskiy A, Liao H-YM, editors. Scaled-yolov4: Scaling cross stage partial network. Proceedings of the IEEE/cvf conference on computer vision and pattern recognition, 13029–13038, 2021.

Ren S, He K, Girshick R, Sun J. Faster r-cnn: Towards real-time object detection with region proposal networks. Adv Neural Inf Process Syst, 9199(10.5555):2969239–2969250, 2015.

Oka S, Nozaki K, Hayashi M. An efficient annotation method for image recognition of dental instruments. Sci Rep, 13(1):169, 2023.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wenkel S, Alhazmi K, Liiv T, Alrshoud S, Simon M. Confidence score: The forgotten dimension of object detection performance evaluation. Sensors, 21(13):4350, 2021.

Article  PubMed  PubMed Central  Google Scholar 

Jin G, Taniguchi R-I, Qu F. Auxiliary detection head for one-stage object detection. IEEE Access, 8:85740-85749, 2020.

Article  Google Scholar