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Tongue Region Based Disease Prediction using Deep Learning

International Journal of Emerging Trends in Science and Technology

Volume 7 Issue 1

Published: 2021
Author(s) Name: S. Kiruthika, P. Sakthi and P. Veeramani | Author(s) Affiliation: Dept. of Electronics and Instrumentation Engg., M.Kumarasamy College of Engg., Karur, Tamil Nadu
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Abstract

Artificial intelligence can learn a few concepts by analyzing tactile information so also to people. It investigates how manufactured neural system (ANNs) can learn unique concepts by analyzing tongue pictures based on concepts, which may be a teach that depends intensely on specialist encounter. A computer-aided strategy will be examined that analyzes tangible information for professionals. It proposes capitalizing on profound learning procedures. A strategy called the conceptual arrangement profound auto encoder (CADAE) is proposed to analyze tongue pictures that speak to diverse body structure (BC) types, which are the basic concepts. Within the first step, CADAE encodes the picture to a representation space; within the moment step, it translates the designs. The tests illustrate that CADAE can learn successful representation of unique concepts adjusted with BC sorts by encoding the tongue pictures. Besides, the representation space of the covered up conceptual neurons can be visualized by a decoder network.

Keywords: CNN, Artificial Intelligence, ANN, Deep Learning

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