Optimized Stack Automated Encoder for Tongue Diabetic Classification

E. Srividhya and Dr.A. Muthukumaravel

Diabetes mellitus (DM) and its difficulties prompting diabetic retinopathy (DR) are soon to end up one of the 21st century's significant medical issues. Tongue finding is one of the imperative region in diagnosing a large portion of the infections, in this manner tongue diagnosing has gotten more criticalness among the specialists. Tongue diagnosing is generally completed by handling the tongue pictures. In this investigation, we proposed a computerized strategy to break down and identify and dissect diabetics by utilizing tongue pictures examination dependent on Particle swarm enhancement with stack auto encoder (PSO-SAE). There is a solid relationship in the middle of the attributes of tongue and human wellbeing conclusion. PSO-SAE are prepared and tried with highlights like surface and chromatic data acquired from tongue picture tests. Proposed philosophy accomplished high exactness by giving applicable information in preparing stage and evacuating unessential information.

Volume 11 | 04-Special Issue

Pages: 2311-2320