Naslov
Gender Estimation from Panoramic Dental X-ray Images using Deep Convolutional Networks

Autori
Ilić, Ivan ; Vodanović, Marin ; Subašić, Marko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Skup
18th IEEE International Conference on Smart Technologies (EUROCON 2019)

Mjesto i datum
Novi Sad, Srbija, 01.07.2019. - 04.07.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
deep convolutional networks ; image classification ; gender estimation ; partial identification ; forensic dentistry

Sažetak
Current techniques for gender estimation from Xray images, except being time-consuming, require a highly experienced expert to perform the process. Deep convolutional neural networks have shown to be a very successful technique in many computer vision tasks, mainly because of high accuracy, stability, and processing speed. In this paper, we propose a new method to the gender estimation from panoramic dental X-ray images based on analysis of images using deep convolutional neural networks trained to perform a binary classification. Detailed insight is provided into architecture, hyperparameters and training procedure of our best performing model obtaining an accuracy of 94.3% on a test set. Further experiments have been performed to get a better understanding of anatomical structures which carry the most important information for gender estimation. The presented method requires no special knowledge or equipment to be used, and besides high accuracy, it is also extremely fast with only 18ms of processing time per image on a dedicated GPU.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Dentalna medicina

POVEZANOST RADA