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Paing, May Phu. Comparison of deep learning-based models for oral disease detection. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2024.
Comparison of deep learning-based models for oral disease detection
Name: Peeranat Thongsakul
Organization :
King Mongkut's Institute of Technology Labkrabang. School of Engineering
Email :
63011249@kmitl.ac.th
Name: Paing, May Phu
Organization :
King Mongkut's Institute of Technology Labkrabang. School of Engineering
Email :
may.pa@kmitl.ac.th
LCSH:
Diagnostic imaging
Abstract:
Background: In contemporary dentistry, oral
object detection is essential for a variety of uses, including
automated dental caries diagnosis and orthodontic treatment
planning. To find the best strategy for dental image analysis, this
study provides a comprehensive comparison of several oral
object detection techniques. Method: Three cutting-edge
deep learning models, including You Only Look Once or YOLO
(especially YOLO V8 and YOLO-NAS), Detection Transformer
or DETR, and Detectron2 were implemented, and their
performances were compared and contrasted to select the most
effective model for dental radiograph image datasets. An opened
dataset of 936 oral X-ray images along with the expert
annotations were applied in the experiment and the model
performances were evaluated in terms of precision, recall, and
F1-score. Results: Experimental findings demonstrated that
Detectron2 outperforms both YOLO and DETR in terms of
detection accuracy, achieving an accuracy of 0.97 and a total loss
of 0.3716 while maintaining real-time inference capabilities.
Furthermore, a mobile application was also developed to port
the model into it and deploy it with Android Studio.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2024
Modified:
2025-05-26
Issued:
2025-05-26
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Thailand Section (IEEE Computer Society Thailand Chapter) and Prince of Songkla University. College of Computing. The 21st International Joint Conference on Computer Science and Software Engineering (JCSSE 2024)) (pp.187-191). Phuket : Prince of Songkla University
eng
©copyrights King Mongkut's University of Technology North Bangkok
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Peeranat Thongsakul
| Title | Contributor | Type |
|---|---|---|
| Comparison of deep learning-based models for oral disease detection
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Peeranat Thongsakul;Paing, May Phu | บทความ/Article |
Paing, May Phu
| Title | Contributor | Type |
|---|---|---|
| Comparison of deep learning-based models for oral disease detection
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Peeranat Thongsakul;Paing, May Phu | บทความ/Article |