Four-category Classification of Human Teeth Based on Wavelet Entropy and Back Propagation Neural Network

DOI

10.2991/icaita-18.2018.15How to use a DOI?

Keywords

teeth classification; back propagation neural network; wavelet entropy; Levenberg-Marquardt algorithm

Abstract

The teeth are natural self-defense weapon of animals. For human, the pronunciation of language is closely related to the upper and lower front teeth (incisors). Furthermore, the cleanliness of the teeth even has an important influence on daily social activities and status of people. Therefore, when the teeth are diseased or need to be corrected, it becomes particularly vital to conduct a precise classification of different teeth in the oral cavity. In this paper, we will introduce our proposed method, back propagation neural network based on wavelet entropy and Levenberg-Marquardt algorithm, to make a correct classification of the teeth. The total accuracy of our method is 83.83± 2.92%. Our method is better than the state-of-art methods in performance.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wenjuan Jia
AU  - Zhi Li
AU  - Wagner Quinn
PY  - 2018/03
DA  - 2018/03
TI  - Four-category Classification of Human Teeth Based on Wavelet Entropy and Back Propagation Neural Network
BT  - Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)
PB  - Atlantis Press
SP  - 58
EP  - 61
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-18.2018.15
DO  - 10.2991/icaita-18.2018.15
ID  - Jia2018/03
ER  -