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Caries Level Classification using K-Nearest Neighbor, Support Vector Machine, and Decision Tree using Zernike Moment Invariant Features
(International Conference on Data Science and Its Applications (ICoDSA), 2022)
Dental caries is the most common disease and is reported as one of the oldest diseases. To avoid the occurrence of dental caries, there are four ways; maintaining oral hygiene, consuming healthy food, adequate fluoride and ...
Algorithm of Caries Level Image Classification using Multilayer Perceptron Based Texture Features
(IEEE International Conference on Cybernetics and Computational Intelligence, 2022)
A number of patients with untreated caries only seek treatment at late stages when serious complications might have already developed and can lead to significant acute and chronic conditions with high cost of treatment. ...
Comparison of Dental Caries Level Images Classification Performance using KNN and SVM Methods
(IEEE, 2021)
This study aims to build a dental caries level classification system based on image processing (i.e. to extract texture features) and machine learning methods. The first step was to analyze and discover the extraction ...
Machine Learnings of Dental Caries Images based on Hu Moment Invariants Features
(International Seminar on Application for Technology of Information and Communication (iSemantic), 2021)
Dental caries generally occurs due to consuming foods containing carbohydrates, such as sucrose, and rarely brushing teeth, thus causing gradual damage to the layers and structures of the teeth. This study aims to build a ...
Classification of Caries X-Ray Images using Multilayer Perceptron Models Based Shape Features
(2022)
Dental caries is one of the diseases that are often experienced by society, one way to detect it by taking pictures using Computed Radiography technology. The aim of this study was to develop a method of classifying dental ...