Dental Diseases Segmentation

International Journal of Electronics and Communication Engineering

© 2022 by SSRG - IJECE Journal

Volume 9 Issue 2

Year of Publication : 2022

Authors : S. Hemalatha, R. Karthika Devi

10.14445/23488549/IJECE-V9I2P101

How to Cite?

S. Hemalatha, R. Karthika Devi, "Dental Diseases Segmentation," SSRG International Journal of Electronics and Communication Engineering, vol. 9,  no. 2, pp. 1-5, 2022. Crossref, https://doi.org/10.14445/23488549/IJECE-V9I2P101

Abstract:

In recent times, dental care detection has been much needed for society. The dental care prediction is performed with innovative automation using Deep learning (DL) techniques. The earlier prediction is the main problem in the dental field that also leads to heavy illness of health. To overcome these issues, segmentation is to be performed effectively. Therefore, this paper presents the DL-based Butterfly-net model to perform an efficient dental care prediction. This butterfly Net algorithm is based on Deep Convolutional Neural Network (DCNN) that is used to classify dental images. This butterfly net algorithm can be evaluated as a dental degree of membership. The proposed work is compared with the previous work where the Butterfly-net has the highest classification accuracy among all.

Keywords:

Dental care, DCNN, Butterfly net, Classification, Prediction.

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