Claim Missing Document
Check
Articles

Found 1 Documents
Search

Penerapan Deep Learning dalam Analisis Citra Gigi Supiyandi Supiyandi; Wahyu Eka Judistira; Sepriana Nurliani; Rondi Sahputra Darmono; Inneke Putri
JURNAL PENDIDIKAN DAN ILMU SOSIAL (JUPENDIS) Vol. 2 No. 4 (2024): Oktober : JURNAL PENDIDIKAN DAN ILMU SOSIAL
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jupendis.v2i4.2165

Abstract

Testing in dental medical recognition and recording is still done manually, causing it to take a long time. In this study, an object detection method was applied to assist doctors in identifying patient conditions. Convolutional Neural Network (CNN) method was trained with an intraoral image dataset that includes five categories of tooth conditions: normal, filling, caries, and residual roots. CNN performance evaluation was conducted using evaluation metrics, and the results showed that the best CNN model achieved an mAP of 84% and a testing accuracy of 82%. This research successfully achieved its main goal, which is to build a reliable deep learning model for dental disease detection and recognition in humans.