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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:

Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network
Shu‐I Pao, Hong-Zin Lin, Ke‐Hung Chien, et al.
Journal of Ophthalmology (2020) Vol. 2020, pp. 1-7
Open Access | Times Cited: 98

Showing 51-75 of 98 citing articles:

Detection of Retinal Abnormalities in OCT Images Using Wavelet Scattering Network
Zahra Baharlouei, Hossein Rabbani, Gerlind Plonka
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022), pp. 3862-3865
Closed Access | Times Cited: 5
Detection of Diabetic Retinopathy Based on Convolutional Neural Networks: A Review
Halbast Rashid Ismael, Adnan Mohsin Abdulazeez, Dathar Abas Hasan
Asian Journal of Research in Computer Science (2021), pp. 1-15
Open Access | Times Cited: 6
Electrocardiographic Machine Learning to Predict Mitral Valve Prolapse in Young Adults
Gen‐Min Lin, Huan-Chang Zeng
IEEE Access (2021) Vol. 9, pp. 103132-103140
Open Access | Times Cited: 6
Detection of Diabetic Retinopathy Image Analysis using Convolution Graph Neural Network
Ramachandran Vignesh, N. Muthukumaran, M. Philip Austin
2022 International Conference on Inventive Computation Technologies (ICICT) (2023), pp. 921-929
Closed Access | Times Cited: 2
Detection of Diabetic Retinopathy from fundus images using Resnet50
Sarvat Ali, Shital Raut
(2023), pp. 1-5
Closed Access | Times Cited: 2
Detection of Diabetic Retinopathy Using Collaborative Model of CNN with IoMT
Hemanta Kumar Bhuyan, Vikash Kumar, Biswajit Brahma
ITM Web of Conferences (2023) Vol. 56, pp. 05008-05008
Open Access | Times Cited: 2
Detection of diabetic retinopathy using AlexNet and lenet CNN models
V Jananee, M. Shanthalakshmi, S. J., et al.
AIP conference proceedings (2023) Vol. 2854, pp. 020014-020014
Closed Access | Times Cited: 2
Hybrid generative model for grading the severity of diabetic retinopathy images
R. Bhuvaneswari, M. Diviya, M. Subramanian, et al.
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (2023) Vol. 11, Iss. 7
Closed Access | Times Cited: 2
ESLO: Enhanced sea lion optimization based bi‐directional CNN‐RNN for accurate detection of diabetic retinopathy
V. Desika Vinayaki, R. Kalaiselvi
Concurrency and Computation Practice and Experience (2022) Vol. 35, Iss. 1
Closed Access | Times Cited: 4
Detecting Diabetes Using Machine Learning Algorithms
Qabeela Q. Thabit, Taqwa Oday Fahad, Alyaa I. Dawood
(2022), pp. 131-136
Closed Access | Times Cited: 3
Deep Learning Approaches for Detecting Diabetic Retinopathy using CNN Models
M. Mukesh Krishnan, S. Ramya, K. Kirubanathavalli, et al.
2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (2022), pp. 1096-1102
Closed Access | Times Cited: 3
Machine learning & deep learning algorithm reviews for diabetic retinopathy detection
Pranali Hatode, Maniroja M Edinburgh
(2022), pp. 164-169
Closed Access | Times Cited: 3
Diabetic Retinopathy Detection and Classification from Fundus Images Using Deep Learning
Pratiksha Shetgaonkar, Shailendra Aswale, Saurabh Naik, et al.
2021 International Conference on Technological Advancements and Innovations (ICTAI) (2021)
Closed Access | Times Cited: 4
An optimized framework for prediagnosis of diabetic retinopathy using HHO-CBL model
Sathyavani Addanki, D. Sumathi
Bratislavské lekárske listy/Bratislava medical journal (2024) Vol. 125, Iss. 03, pp. 196-205
Open Access
HR-NET: Revolutionizing Diabetic Retinopathy Diagnosis with High-Resolution Analysis
Azmiza Syawani Jasni, I Sowmy
International Journal of Electronics and Communication Engineering (2024) Vol. 11, Iss. 7, pp. 65-76
Open Access
Diabetic Retinopathy Identification Using Optimized Deep CNN Classifier
Archana Senapati, Hrudaya Kumar Tripathy
(2024) Vol. 3, pp. 199-206
Closed Access
You Only Look Once (YOLO) with Convolution Neural Network (CNN) Classification for Preterm Baby’s Retinopathy Images
Gilles Hubert, S. Silvia Priscila
Communications in computer and information science (2024), pp. 367-377
Closed Access
Classification of Diabetic Retinopathy Disease Levels by Extracting Spectral Features Using Wavelet CNN
Sumod Sundar, S. Sumathy, Mufti Mahmud
Diagnostics (2024) Vol. 14, Iss. 11, pp. 1093-1093
Open Access
Comparison of Preprocessing Methods Impact on Detection of Soldering Splashes Using Different YOLOv8 Versions
Peter Klčo, Dušan Koniar, Libor Hargaš, et al.
Research Square (Research Square) (2024)
Open Access
Convolutional Neural Network Model for Diabetic Retinopathy Feature Extraction and Classification
Sharan Subramanian, Leilani H. Gilpin
Journal of Student Research (2024) Vol. 13, Iss. 1
Open Access
Detection of Diabetic Retinopathy (DR) Severity from Fundus Photographs using Conv-ViT
Dheeraj Chintamreddy, Usha Rani Seshasayee
(2024), pp. 1-6
Closed Access
A Nature Inspired Optimization for Retinal Lesion Detection
Kanchan S. Gorde, Ajay A. Gurjar
Journal of Advances in Information Technology (2024) Vol. 15, Iss. 10, pp. 1148-1156
Open Access
Comparison of Preprocessing Method Impact on the Detection of Soldering Splashes Using Different YOLOv8 Versions
Peter Klčo, Dušan Koniar, Libor Hargaš, et al.
Computation (2024) Vol. 12, Iss. 11, pp. 225-225
Open Access
DRSegNet: A cutting-edge approach to Diabetic Retinopathy segmentation and classification using parameter-aware Nature-Inspired optimization
Sundreen Asad Kamal, Youtian Du, Majdi Khalid, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0312016-e0312016
Open Access
Detection and Classification of Diabetic Retinopathy Using Image Processing and Machine Learning Techniques
G. Nadar, Kavita Sonawane
Smart innovation, systems and technologies (2023), pp. 33-46
Closed Access | Times Cited: 1

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