Identification And Classification of Dental Malocclusions By Utilizing YOLO Algorithm

Abstract

To develop a web application for potential malocclusion patients, that provides a generated report on the state of their occlusive health by entering an image of their teeth. The implemented system uses a set of trained YOLO models to detect the type of malocclusion, the severity, and the condition's location. Using the detection the system creates a report that provides the user with information on the results and explains their condition and what they can expect for treatment.