Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks

Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks

Abstract Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stages. Manual diagnosis is labor-intensive and prone to inaccuracies, highlighting the need for automated, accurate detection methods. This stud...

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Bibliographic Details
Main Authors: Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
African vulture optimization
Attention mechanism based capsule network
Diabetic retinopathy
Hopfield neural network
Electric fish optimization
Bilinear convolutional attention network
Online Access:https://doi.org/10.1038/s41598-025-99228-w
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https://doi.org/10.1038/s41598-025-99228-w

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