Multi-Class Retinal Diseases Detection Using Deep CNN With Minimal Memory Consumption-Reference-Cited by-同舟云学术

Multi-Class Retinal Diseases Detection Using Deep CNN With Minimal Memory Consumption

Author:

Nawaz Asif¹^ORCID,Ali Tariq¹^ORCID,Mustafa Ghulam¹^ORCID,Babar Muhammad²^ORCID,Qureshi Basit³^ORCID

Affiliation:

1. University Institute of Information Technology (UIIT), PMAS-Arid Agriculture University, Rawalpindi, Pakistan

2. Robotics and Internet of Things Laboratory, Prince Sultan University (PSU), Riyadh, Saudi Arabia

3. College of Computer and Information Sciences, Prince Sultan University (PSU), Riyadh, Saudi Arabia

Funder

Prince Sultan University, Riyadh, Saudi Arabia, for the payment of Article Processing Charges for this research work

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference38 articles.

2. Adam: A method for stochastic optimization;kingma;arXiv 1412 6980,2014

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

4. OcuVision:CNN powered Analysis of Retinal images for Disease Diagnosis;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

5. Cotton Plant Disease Prediction and Remedy Recommendation System;2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS);2024-01-28