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Ocular Disease Intelligent Recognition using Hybrid CNN Approach
¹²³ MSc (Integrated) Decision and Computing Sciences, Coimbatore Institute of Technology, Tamilnadu, India. ⁴Associate Professor, Department of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India. ⁵ Assistant Professor, Department of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India.
Published Online: May-June 2022
Pages: 469-472
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Abstract
View PDFAbstract: Ocular disease early detection is an economic and productive path to forestall visual defect caused by diabetes, glaucoma, cataract, age-related devolution (AMD), and plenty of other diseases. Currently according to planet Health Organization (WHO), a minimum of 2 billion people round the world have vision impairments, of whom a minimum of 1 billion have a vision impairment that might are prevented. Speedy and automatic detection of diseases is critical and urgent in reducing the ophthalmologist’s workload and prevents vision damage of patients. Computer vision and deep learning can automatically detect ocular diseases by providing high-quality medical eye fundus images.
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