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This work is licensed under a Creative Commons Attribution 4.0 International License.
DIABETIC RETINOPATHY DETECTION USING VGG-NIN A DEEP LEARNING
DEEPAKRAJ.M, DHIVYA.PV, SATHYASEELAN.M, SHABARI.M, Dr. N . KOTTISWARAN, M.E., Ph.D, Dr. P. D. R VIJAYAKUMAR, M.E., Ph. D, Mrs. P. GOKILA, M.E, Mrs. A. SARANYA, M.E
DOI: 10.17148/IJARCCE.2023.12559
Abstract:
Diabetic Retinopathy (DR) is a disease that damages retinal blood vessels and leads to blindness. Usually, colored fundus shots are used to diagnose this irreversible disease. The manual analysis (by clinicians) of the mentioned images is monotonous and error-prone. Hence, various computer vision hands-on engineering techniques are applied to predict the occurrences of the DR and its stages automatically. The VGG16, spatial pyramid pooling layer (SPP) and network-in-network (NiN) are stacked to make a highly nonlinear scale-invariant deep model called the VGG-NiN model. The proposed VGG-NiN model can process a DR image at any scale due to the SPP layerβs virtueπ 14 views
This work is licensed under a Creative Commons Attribution 4.0 International License.How to Cite:
[1] DEEPAKRAJ.M, DHIVYA.PV, SATHYASEELAN.M, SHABARI.M, Dr. N . KOTTISWARAN, M.E., Ph.D, Dr. P. D. R VIJAYAKUMAR, M.E., Ph. D, Mrs. P. GOKILA, M.E, Mrs. A. SARANYA, M.E, βDIABETIC RETINOPATHY DETECTION USING VGG-NIN A DEEP LEARNING,β International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12559