A REVIEW PAPER ON IDENTIFYING CORNEAL DISEASES BY OCULAR SURFACE PHOTOGRAPHS USING DEEP LEARNING









Abstract

The Ocular diseases has affected many million individuals. So, there’s ought to develop a replacementquick eye disease screening technique with the simpler access and lower price. There are a lot of ocularmanifestations that are reportable within the disease patients as growing clinical proof. We tend to propose a replacement quick screening technique of analyzing the eye- region pictures, captured by common CCD and CMOS cameras. This might faithfully build a fast risk screening ofdisease with the property stable high performance in several countries and races. Our model for disease fast prescreening have the deserves of the lower price, absolutely selfperformed, non-invasive, significantly real time, and so permits the continual health detecting. We tend to more implement it because the open accessible arthropod genus, and supply public service to the globe. Our pilot experiments show that our model is prepared to be usable to all or any varieties of detecting situations, like infrared temperature measuring device at airports and stations. Blurred vision, burning, excessive tearing, and an unsmooth feeling, almost as if there is sand in the eye are all symptoms of Oxygen deficiency in the eyes. Swelling inside the animal tissue layer of the membrane and transient impaired vision are common in mild cases.


Modules


Algorithms


Software And Hardware