Web-Based Dental Caries Detection Using a Convolutional Neural Network and OpenCV

2025-09-19T08:39:24+00:00

Early detection of dental caries presents a significant challenge, particularly in regions with limited access to healthcare services. While many AI models focus on binary classification, real-world applications must handle irrelevant inputs to be robust. This study develops and evaluates a web-based system using a Convolutional Neural Network (CNN) for a three-class dental image classification task: 'Caries', 'No Caries', and 'Not a Tooth'. The method employs transfer learning with the MobileNetV3 Small architecture, trained on a custom augmented dataset of 5,811 images. The model was implemented into an accessible web application using the Flask framework and OpenCV library, supporting both image upload and real-time detection. On the test set, the model achieved an overall accuracy of 93%. It demonstrated exceptional performance in rejecting irrelevant images and high reliability in identifying caries. This study presents a practical and robust tool for initial dental screening, highlighting the importance of a dedicated 'non-target' class for building trustworthy real-world AI applications in tele-dentistry.

Interpretation of the Subsurface Structure of Batanta Island Using Gravity Method and 2D Modeling

2025-10-15T03:50:47+00:00

Batanta Island in Raja Ampat, West Papua, is located in an active tectonic zone dominated by fault structures and igneous rock intrusions, thus possessing significant geological potential. This research aims to identify the subsurface structure of the island using the gravity method that has undergone drift, tidal, topographic, and Bouguer corrections, followed by regional-residual component separation. 2D modeling with GM-SYS software was used to construct geological cross-sections based on rock density distribution. Results show the presence of several main units, including massive lava, breccia, Quaternary deposits, and high-density intrusion bodies (±3.00 g/cm³) that are interpreted as diorite. An active fault zone and lithological boundary were also found, which serve as the main controllers of geological structure. These findings indicate the presence of mineralization potential and complex geological dynamics, and serve as an important initial contribution to further geological exploration on Batanta Island and its surroundings

Jurnal Teknologi Informasi dan Pendidikan

Web-Based Dental Caries Detection Using a Convolutional Neural Network and OpenCV

Interpretation of the Subsurface Structure of Batanta Island Using Gravity Method and 2D Modeling