An Intelligent Moth Flame Optimization with Inception Network for Diabetic Retinopathy Detection and Grading
Author:
Affiliation:
1. College of Computer Science and Information Technology, Tabuk Univesity,Saudi Arabia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9711508/9711541/09711602.pdf?arnumber=9711602
Reference17 articles.
1. An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading
2. Hyperparameter Tuning Deep Learning for Diabetic Retinopathy Fundus Image Classification
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4. Deep-learning-based automatic computer-aided diagnosis system for diabetic retinopathy
5. Deep neural network with moth search optimization algorithm based detection and classification of diabetic retinopathy images
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1. Research Progress and Prospects of Intelligent Diabetes Monitoring Systems: A Review;IEEE Sensors Journal;2024-08-01
2. Hyperparameter optimization of pre-trained convolutional neural networks using adolescent identity search algorithm;Neural Computing and Applications;2023-11-09
3. Hybrid generative model for grading the severity of diabetic retinopathy images;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2023-10-15
4. Internet of Things and Deep Learning Enabled Diabetic Retinopathy Diagnosis Using Retinal Fundus Images;IEEE Access;2023
5. A Deep Learning Based Approach for Grading of Diabetic Retinopathy Using Large Fundus Image Dataset;Diagnostics;2022-12-07
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