Identification And Classification Of Eye Disease Using Deep Learning

Abstract

As The World Is Moving Into The World Of Technology Classification Of The Eye Disease Is Considered To Be Having A Clinical Use As It Evaluate And Analysis The Results. Requirements For The Classification Of The Eye Disease Should Be Simple In Nature, Structure And Evaluation. Diabetics Retinopathy Is One Of The Most Widely Spreading Eye Diseases Which Is Found In People With Diabetics, It Is Caused By Damaging The Blood Vessels In The Retina Which Began To Leak Fluids And Blood When This Fluid Leaks It Causes Macular To Swell Or Thicken Which Raises To Disease Called Diabetic Macular Edema (Dme). Glaucoma Is One Among  The Leading Causes Of Unchangeable Vision Loss Which Is Additionally One Among The Various Approaches Have Recently Been Proposed For Automatic Glaucoma And Diabetic Macular Edema Detection Based On Fundus Images.Using Convolutional Neural Network Which Is The Classification Of Deep Learning, Can Conclude A Hierarchical Representation Of Images To Classify Between Normal And Diseased Eye Patterns For Diagnostic Decisions .Thus The Target Of This  Paper Is To Implement And Define The Deep Learning To Identify And Classify The Eye Disease.