DETECTION OF OCULAR EYE DISEASE FROM BIGDATA USING DEEP CONVOLUTIONAL NEURAL NETWORK
Abstract
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In this paper, we present a neural network models like artificial neural network (ANN), back propagation neural network (BPNN), feed forward neural network (FFNN) and Long Short Term Memory (LSTM) named Recurrent Neural Network (RNN) to classify the input images using a series of frameworks. The architecture involves data collection, pre-processing, feature extraction and classification of images. A 10-fold cross validation is conducted on the collected input image samples and the results are evaluated against these four models over different performance metrics. The results show that the RNN attains improved classification accuracy and reduced error rate than other methods.

Authors
M Sangeetha
Cochin University of Science and Technology, India

Keywords
Ocular Eye Disease, Neural Network Framework, Machine Learning, Classification
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Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 2 , Issue: 2 , Pages: 184-187 )
Date of Publication :
March 2021
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94
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