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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 Hybrid Technique for Diabetic Retinopathy Detection Based on Ensemble-Optimized CNN and Texture Features
Uzair Ishtiaq, Erma Rahayu Mohd Faizal Abdullah, Zubair Ishtiaque
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1816-1816
Open Access | Times Cited: 17

Showing 17 citing articles:

Diabetic retinopathy detection and severity classification using optimized deep learning with explainable AI technique
B. Lalithadevi, S. Krishnaveni
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 10
Diabetic retinopathy detection using ensembled transfer learning based thrice CNN with SVM classifier
Neetha Merin Thomas, S. Albert Jerome
Multimedia Tools and Applications (2024) Vol. 83, Iss. 27, pp. 70089-70115
Closed Access | Times Cited: 7
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
Advanced Hybridization and Optimization of DNNs for Medical Imaging: A Survey on Disease Detection Techniques
Maneet Kaur Bohmrah, Harjot Kaur
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open 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
A Systematic Review on Fundus Image-Based Diabetic Retinopathy Detection and Grading: Current Status and Future Directions
Amna Ikram, Azhar Imran, Jianqiang Li, et al.
IEEE Access (2024) Vol. 12, pp. 96273-96303
Open Access | Times Cited: 3
Optimal Artificial Neural Network-based Fabric Defect Detection and Classification
N. Sajitha, S. Prasanna Priya
Engineering Technology & Applied Science Research (2024) Vol. 14, Iss. 2, pp. 13148-13152
Open Access | Times Cited: 2
Diabetic retinopathy detection using EADBSC and improved dilated ensemble CNN-based classification
Neetha Merin Thomas, S. Albert Jerome
Multimedia Tools and Applications (2023) Vol. 83, Iss. 11, pp. 33573-33595
Closed Access | Times Cited: 6
Application of deep learning and feature selection technique on external root resorption identification on CBCT images
Nor Hidayah Reduwan, Azwatee Abdul Aziz, Roziana Mohd Razi, et al.
BMC Oral Health (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Radiomics in ophthalmology: a systematic review
Haiyang Zhang, Huijie Zhang, Mengda Jiang, et al.
European Radiology (2024)
Closed Access | Times Cited: 1
An Ensemble Deep Learning Model for Diabetic Retinopathy Identification
Mohammad Manzoor Hussain, P. Shanmugam, K. Moorthi, et al.
2022 8th International Conference on Smart Structures and Systems (ICSSS) (2023)
Closed Access | Times Cited: 2
Enhancing Cataract Detection through Hybrid CNN Approach and Image Quadration: A Solution for Precise Diagnosis and Improved Patient Care
Van‐Viet Nguyen, Chun‐Ling Lin
Electronics (2024) Vol. 13, Iss. 12, pp. 2344-2344
Open Access
Bibliometric analysis of ophthalmic OCT and OCT angiography research trends over the past 20 years
Qian Qian, Jing Wang
International Ophthalmology (2024) Vol. 44, Iss. 1
Closed Access
Blood Vessel Segmentation and Classification of Diabetic Retinopathy with Machine Learning-Based Ensemble Model
Cihan AKYEL, Bünyamin Ciylan
Journal of Advanced Research in Natural and Applied Sciences (2024) Vol. 10, Iss. 3, pp. 560-570
Closed Access
Is Automated Machine Learning useful for ocular toxoplasmosis identification and classification of the inflammatory activity?
Carlos Cifuentes‐González, William Rojas‐Carabali, Germán Mejía‐Salgado, et al.
Deleted Journal (2024), pp. 100079-100079
Open Access
FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy
Dasari Bhulakshmi, Dharmendra Singh Rajput
PeerJ Computer Science (2024) Vol. 10, pp. e2508-e2508
Open Access
Diabetic eye disease in computerised tomography of feature extraction and classification in hybrid neural network
Michela Vespa, C.Agees Kumar
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (2023) Vol. 12, Iss. 1
Open Access | Times Cited: 1
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