Abstract
Eyes are our body's most importantly developed sensory organ. A far large part of the brain is dedicated to vision, other sensory activities such as hearing, taste, touch, or smell combined. This precious organs affected by various reasons. Glaucoma is a category of eye disease that causes damages to the optic nerves, the protection of which is critical for proper vision. This collision is often triggered by unusually high pressure in your eye. Glaucoma also known as the “Silent Thief of Sight,” is one of the leading cause of blindness in the world for people above the age of 60.The cost of detecting glaucoma using optical coherence tomography (OCT) and Heidelberg Retinal Tomography (HRT) technique is prohibitively high. The aim of this study is to uncover and explore the early detection of glaucoma using the Support Vector Machine (SVM) classifier process, which are a type of Supervised learning method. Furthermore, the SVM classification process is straightforward, with high precision and first-rate performance.
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