International Journal of Emerging Trends in Science & Technology

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Tongue Region Based Disease Prediction using Deep Learning


Affiliations
1 Assistant Professor, Department of Electronics and Instrumentation Engineering, MKumarasamy College of Engineering, Karur, Tamil Nadu, India
2 Assistant Professor, Department of Electronics and Instrumentation Engineering, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, India
     

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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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  • Tongue Region Based Disease Prediction using Deep Learning

Abstract Views: 185  |  PDF Views: 0

Authors

S. Kiruthika
Assistant Professor, Department of Electronics and Instrumentation Engineering, MKumarasamy College of Engineering, Karur, Tamil Nadu, India
P. Sakthi
Assistant Professor, Department of Electronics and Instrumentation Engineering, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, India
P. Veeramani
Assistant Professor, Department of Electronics and Instrumentation Engineering, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, India

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

References