HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification

HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification

Abstract Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventional CNN-based models face limitations such as high computational overhead, noise sensitivity, and data imbalance. This paper introduces HDL-ACO, a novel Hybrid Deep Learning (HDL) framework t...

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Bibliographic Details
Main Authors: Shivani Agarwal, Anand Kumar Dohare, Pranshu Saxena, Jagendra Singh, Indrasen Singh, Umesh Kumar Sahu
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Optical coherence tomography
Hybrid deep learning
Ant colony optimization
Hyperparameter tuning
Data Imbalance
OCT image classification
Online Access:https://doi.org/10.1038/s41598-025-89961-7
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https://doi.org/10.1038/s41598-025-89961-7

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