Abstract
Dental Shade Matching Method Based on Hue, Saturation, Value Color Model with Machine Learning and Fuzzy Decision
Highlights
The techniques of big data analysis and machine learning are used widely in medicine [detecting pneumonia,(1) autism,(2) and risk of falling,(3) the classification of cancers,(4) and the analysis of cell pseudo-color images(5)]
To avoid the above-mentioned problems caused by manual judgment, we propose an image processing technique for color matching
The results indicated an improved accuracy of 92.31%, which is significantly higher than the accuracy of only 32.69% of previous methods
Summary
The techniques of big data analysis and machine learning are used widely in medicine [detecting pneumonia,(1) autism,(2) and risk of falling,(3) the classification of cancers,(4) and the analysis of cell pseudo-color images(5)]. A method of dental image analysis is developed in this study. Most well-known algorithms use machine learning for training and classification. When a feature vector is compromised and used to store biometric information, through deep learning, a machine-learning-based biometric recognition system can ensure accurate results. The diagnosis of specific malignancies uses artificial intelligence (AI) techniques to classify symptoms and distinguish whether samples are clean or infected.(11) The results are classified on the basis of promise training and may enable the diagnosis of lymph node malignancy in clinical trials. Hsia(12) used binary robustness as a feature of finger vein recognition as a new verification strategy. Finger veins were shown to be a much more stable feature than other biometrics that cannot be copied or stolen
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