ODMNet: Automated Glaucoma Detection and Classification Model Using Heuristically-Aided Optimized DenseNet and MobileNet Transfer Learning-Reference-Cited by-同舟云学术

ODMNet: Automated Glaucoma Detection and Classification Model Using Heuristically-Aided Optimized DenseNet and MobileNet Transfer Learning

Published:2023-02-03 Issue:1 Volume:55 Page:245-277
ISSN:0196-9722
Container-title:Cybernetics and Systems
language:en
Short-container-title:Cybernetics and Systems

Author:

Xavier Felix Joseph¹,F. Fanax Femy²

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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