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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Lightweight Diabetic Retinopathy Detection Model Using a Deep-Learning Technique
Abdul Rahaman Wahab Sait
Diagnostics (2023) Vol. 13, Iss. 19, pp. 3120-3120
Open Access | Times Cited: 14

Showing 14 citing articles:

Diabetic Retinopathy Classification With Deep Learning via Fundus Images: A Short Survey
Shanshan Zhu, Changchun Xiong, Qingshan Zhong, et al.
IEEE Access (2024) Vol. 12, pp. 20540-20558
Open Access | Times Cited: 11
Automatic Diabetic Retinopathy Identification Using the Zernike Moment Decomposition in Fundus Images
Javier Almeida, I. J. Orlando Guerrero
IFMBE proceedings (2025), pp. 259-269
Closed Access
Diabetic retinopathy detection via exudates and hemorrhages segmentation using iterative NICK thresholding, watershed, and Chi2 feature ranking
Patsaphon Chandhakanond, Pakinee Aimmanee
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Optimal Convolutional Networks for Staging and Detecting of Diabetic Retinopathy
Minyar Sassi Hidri, Adel Hidri, Suleiman Ali Alsaif, et al.
Information (2025) Vol. 16, Iss. 3, pp. 221-221
Open Access
Reliable and Energy-Efficient Diabetic Retinopathy Screening Using Memristor-Based Neural Networks
Sumit Diware, Koteswararao Chilakala, Rajiv Joshi, et al.
IEEE Access (2024) Vol. 12, pp. 47469-47482
Open Access | Times Cited: 4
Diabetic Retinopathy Detection Using DL‐Based Feature Extraction and a Hybrid Attention‐Based Stacking Ensemble
Sanjana Rajeshwar, Shreya Thaplyal, M. S. Anbarasi, et al.
Advances in Public Health (2025) Vol. 2025, Iss. 1
Open Access
FEATURES OF THE MODIFICATION OF THE INCEPTIONRESNETV2 ARCHITECTURE AND THE CREATION OF A DIAGNOSTIC SYSTEM FOR DETERMINING THE DEGREE OF DAMAGE TO RETINAL VESSELS
Dmytro Prochukhan
Computer Systems and Information Technologies (2024), Iss. 1, pp. 27-32
Open Access
Predicting Diabetic Retinopathy Severity with Deep Learning: A Survey of Fundus Image Analysis Technique
A Binusha Sornil, C. Sheeja Herobin Rani, I.Rexilin Sheeba
(2024)
Closed Access
Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images
Roseline Oluwaseun Ogundokun, Joseph Bamidele Awotunde, Hakeem Babalola Akande, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 80, Iss. 1, pp. 139-161
Open Access
Automated Diabetic Retinopathy Identification Through Deep Learning Methods
Ashok Kumar Kavuru, Rajesh Kumar Patjoshi
(2024), pp. 1-6
Closed Access
Data-driven 2D-EWT based diabetic retinopathy identification using hybrid neural network
Amit Rawat, Maheshwari Prasad Singh, Rishi Raj Sharma
Image and Vision Computing (2024) Vol. 150, pp. 105194-105194
Closed Access
Artificial Intelligence (AI)-Enhanced Detection of Diabetic Retinopathy From Fundus Images: The Current Landscape and Future Directions
Lara Alsadoun, Husnain Ali, Muhammad Muaz Mushtaq, et al.
Cureus (2024)
Open Access
A Novel Automated System for Early Diabetic Retinopathy Detection and Severity Classification
Santoshkumar S Ainapur, Vedashri Patil
Journal of Chemometrics (2024) Vol. 38, Iss. 11
Open Access
Pavement Binder Course Optimization
Abrar Alazawi, Hassan Musa Al-Mousawi
Al-Nahrain Journal for Engineering Sciences (2024) Vol. 27, Iss. 2, pp. 155-163
Open Access
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