ODMNet: Automated Glaucoma Detection and Classification Model Using Heuristically-Aided Optimized DenseNet and MobileNet Transfer Learning
Author:
Affiliation:
1. Department of Electrical and Electronics Engineering, Bethlahem Institute of Engineering, Karungal, India
2. Department of Computer Science, Holy Cross College (Autonomous), Nagercoil, India
Publisher
Informa UK Limited
Subject
Artificial Intelligence,Information Systems,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/01969722.2023.2166250
Reference51 articles.
1. A Review on Glaucoma Disease Detection Using Computerized Techniques
2. Automated Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features
3. The Use of U-Net Lite and Extreme Gradient Boost (XGB) for Glaucoma Detection
4. A Comparative Study of Deep Learning Models for Diagnosing Glaucoma From Fundus Images
5. Ambati L. S. K Narukonda G. R. Bojja and D. Bishop 2020. Factors influencing the adoption of artificial intelligence in organizations - From an employee’s perspective. MWAIS 2020 Proceedings.
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1. Fundus Imaging-Based Healthcare: Present and Future;ACM Transactions on Computing for Healthcare;2023-07-31
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