Human Age Estimation Through Panoramic Radiographs Images With Deep Neural Network

Example Results: WebApp(Prototype)

Input-output

Abstract

   Estimating dental age in children and adolescents is important for diagnostic planning. Dental and orthodontic treatment, especially in persons of biological age. And physiological age inconsistencies. Age estimation is also part of the forensic approach. For age prediction in the case of refugees, child molesting Age fake Age estimation is therefore important for the deceased person. Living persons, children, adolescents, and adults, as well as the identity of a living or deceased person, must be identified to raise legal suspicions. Estimating human age from panoramic radiographs is difficult and requires considerable expertise in dentistry. Nowadays, AI is increasingly used in medicine because it is faster, more accurate, and more precise than humans can be.
  The developer has developed a system for determining the age of humans from panoramic radiographs. The development team has used deep learning to help develop a model that will be used in the panoramic radiographic human age detection system to achieve the highest accuracy. It is also a time-saving tool. And reduce dental errors. This research aims to develop a web application to check out the human in panoramic photos.
  Research Benefits The estimation of human age through panoramic X-ray images using deep learning techniques is intended to help understand the tooth structure of people of different sexes and age ranges, and this web application will be a tool for that. That saves time and reduces dentist errors as well.

Project poster

Honorable Mention in The 25th National Software Contest