Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Ensemble of multi-stage deep convolutional neural networks for automated grading of diabetic retinopathy using image patches
V. Deepa, C. Sathish Kumar, Thomas Cherian
Journal of King Saud University - Computer and Information Sciences (2021) Vol. 34, Iss. 8, pp. 6255-6265
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Detection of Diabetic Retinopathy using Convolutional Neural Networks for Feature Extraction and Classification (DRFEC)
Dolly Das, Saroj Kumar Biswas, Sivaji Bandyopadhyay
Multimedia Tools and Applications (2022) Vol. 82, Iss. 19, pp. 29943-30001
Open Access | Times Cited: 70
Improved prostate cancer diagnosis using a modified ResNet50-based deep learning architecture
Fatma M. Talaat, Shaker El–Sappagh, Khaled Alnowaiser, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 18
Deep Learning and Medical Image Processing Techniques for Diabetic Retinopathy: A Survey of Applications, Challenges, and Future Trends
Posham Uppamma, Sweta Bhattacharya
Journal of Healthcare Engineering (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 26
Enhancing diabetic retinopathy detection through preprocessing and feature extraction with MGA-CSG algorithm
Ramya Navaneethan, Hemavathi Devarajan
Expert Systems with Applications (2024) Vol. 249, pp. 123418-123418
Closed Access | Times Cited: 9
Deep learning model using classification for diabetic retinopathy detection: an overview
Dharmalingam Muthusamy, Parimala Palani
Artificial Intelligence Review (2024) Vol. 57, Iss. 7
Open Access | Times Cited: 7
A Regression-Based Approach to Diabetic Retinopathy Diagnosis Using Efficientnet
Midhula Vijayan, S Venkatakrishnan
Diagnostics (2023) Vol. 13, Iss. 4, pp. 774-774
Open Access | Times Cited: 15
ResViT FusionNet Model: An explainable AI-driven approach for automated grading of diabetic retinopathy in retinal images
Amna Ikram, Azhar Imran
Computers in Biology and Medicine (2025) Vol. 186, pp. 109656-109656
Closed Access
Enhancing Segmentation Accuracy of Diabetic Retinal Images Using Transform Techniques and deepLabV3+ with Ensemble Classification
S. Saranya, T. Pranesh, R. Rajasurya, et al.
Lecture notes in networks and systems (2025), pp. 179-190
Closed Access
Dual-Path and Multi-Scale Enhanced Attention Network for Retinal Diseases Classification Using Ultra-Wide-Field Images
Fangsheng Chen, Shaodong Ma, Jinkui Hao, et al.
IEEE Access (2023) Vol. 11, pp. 45405-45415
Open Access | Times Cited: 11
Detecting Fundus Lesions for Diabetic Retinopathy (DR) Analysis
Soumya H. Hooli, Yashaswini S. Murgod, Kaveri S. Haramagatti, et al.
Lecture notes in networks and systems (2025), pp. 261-271
Closed Access
Dual-stage dynamic hierarchical attention framework for saliency-aware explainable diabetic retinopathy grading
Shilpa Elsa Abraham, Binsu C. Kovoor
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110364-110364
Closed Access
A multi model deep net with an explainable AI based framework for diabetic retinopathy segmentation and classification
Neeraj Sharma, Praveen Lalwani
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Diabetic Retinopathy Detection with Deep Learning: A ResNet-CNN Model Enhanced by Attention Mechanism and Ensemble Learning
Nor Hazlyna Harun, S. N. Fathiyah Jamaludin, Nur Hafizati Mohtar
Open Journal of Applied Sciences (2025) Vol. 15, Iss. 03, pp. 688-699
Open Access
Classification of diabetic retinopathy based on improved deep forest model
Xiwen Qin, Dongxue Chen, Yichang Zhan, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104020-104020
Closed Access | Times Cited: 16
A Comprehensive Review of Diabetic Retinopathy Detection and Grading Based on Deep Learning and Metaheuristic Optimization Techniques
A. Mary Dayana, W. R. Sam Emmanuel
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 7, pp. 4565-4599
Closed Access | Times Cited: 9
Machine Learning Styles for Diabetic Retinopathy Detection: A Review and Bibliometric Analysis
Shyamala Subramanian, Sashikala Mishra, Shruti Patil, et al.
Big Data and Cognitive Computing (2022) Vol. 6, Iss. 4, pp. 154-154
Open Access | Times Cited: 13
Deep learning based diabetic retinopathy screening for resource constraint applications
Majida Kazmi, Basra Hafeez, Duae Fatima, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 33, pp. 79559-79588
Closed Access | Times Cited: 2
Deciphering the impact of diversity in CNN-based ensembles on overcoming data imbalance and scarcity in medical datasets: A case study on diabetic retinopathy
Inamullah, Saima Hassan, Samir Brahim Belhaouari, et al.
Informatics in Medicine Unlocked (2024) Vol. 49, pp. 101557-101557
Open Access | Times Cited: 2
Disease Grading of Diabetic Retinopathy using Deep Learning Techniques
Anitha T. Nair, Anitha M. L, Arun Kumar M. N.
2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (2022), pp. 1019-1024
Closed Access | Times Cited: 11
Application of deep learning approaches for classification of diabetic retinopathy stages from fundus retinal images: a survey
Nilarun Mukherjee, S. Sengupta
Multimedia Tools and Applications (2023) Vol. 83, Iss. 14, pp. 43115-43175
Closed Access | Times Cited: 6
Hybrid Framework for Diabetic Retinopathy Stage Measurement Using Convolutional Neural Network and a Fuzzy Rules Inference System
Rawan Ghnemat
Applied System Innovation (2022) Vol. 5, Iss. 5, pp. 102-102
Open Access | Times Cited: 9
Diabetic retinopathy grading review: Current techniques and future directions
Wadha Almattar, Hamzah Luqman, Fakhri Alam Khan
Image and Vision Computing (2023) Vol. 139, pp. 104821-104821
Closed Access | Times Cited: 5
Detecting diabetic retinopathy using a hybrid ensemble XL machine model with dual weighted-Kernel ELM and improved mayfly optimization
K Anitha, P Shanmuga Prabha, K. Sashi Rekha, et al.
Expert Systems with Applications (2024) Vol. 253, pp. 124221-124221
Closed Access | Times Cited: 1
Multi-class Diabetic Retinopathy Classification Using Transfer Learning and MixUp Data Augmentation
Fatima Zahra El Yadari, Hiba Chougrad, Youness Idrissi Khamlichi
(2024), pp. 309-316
Closed Access | Times Cited: 1
Evaluating the Performance of a Non-Uniform Squash Function in Capsule Networks for Early Diabetic Retinopathy Detection Using Fundus Image Analysis
Nagachandrika Gogulamudi, G. Madhu, Apparao Naidu G, et al.
Results in Engineering (2024) Vol. 23, pp. 102820-102820
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top