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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:

Supervised fine-tuned approach for automated detection of diabetic retinopathy
Kriti Ohri, Mukesh Kumar
Multimedia Tools and Applications (2023) Vol. 83, Iss. 5, pp. 14259-14280
Closed Access | Times Cited: 15

Showing 15 citing articles:

Llama 2: Early Adopters' Utilization of Meta's New Open-Source Pretrained Model
Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios Κ. Nasiopoulos
(2023)
Open Access | Times Cited: 25
Deep Learning in Automatic Diabetic Retinopathy Detection and Grading Systems: A Comprehensive Survey and Comparison of Methods
Israa Y. AbuShawish, Sudipta Modak, Esam Abdel‐Raheem, et al.
IEEE Access (2024) Vol. 12, pp. 84785-84802
Open Access | Times Cited: 12
Seeing Beyond: Advanced Image and Thermal Analysis for Early Detection of Diabetic Retinopathy and Diabetes
Arvind Mewada, Sushil K. Maurya, M. A. Ansari
Biomedical & Pharmacology Journal (2025) Vol. 18, Iss. December Spl Edition, pp. 191-202
Open Access | Times Cited: 1
Llama 2: Early Adopters' Utilization of Meta's New Open-Source Pretrained Model
Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios Κ. Nasiopoulos
(2023)
Open Access | Times Cited: 11
Segmentation Using the IC2T Model and Classification of Diabetic Retinopathy Using the Rock Hyrax Swarm-Based Coordination Attention Mechanism
B. N. Jagadesh, M. Karthik, Dharmapuri Siri, et al.
IEEE Access (2023) Vol. 11, pp. 124441-124458
Open Access | Times Cited: 10
Adaptive Fusion Attention for enhanced classification and interpretability in medical imaging
Nagur Shareef Shaik, N. Veeranjaneulu, Jyostna Devi Bodapati
Machine Vision and Applications (2025) Vol. 36, Iss. 3
Closed Access
A novel fusion approach with a robust ParallelNet model for diabetic retinopathy diagnosis
Haroon Mahmood, Saad Ather, Aamir Wali, et al.
Pattern Analysis and Applications (2025) Vol. 28, Iss. 2
Closed Access
Enhanced Diabetic Retinopathy Detection Mechanism Through Ensemble Learning Techniques
Kapil Chaturvedi, Vijay Bhandari, Ashutosh Kothari, et al.
Learning and analytics in intelligent systems (2025), pp. 17-37
Closed Access
Enhancing multi-class diabetic retinopathy detection using tuned hyper-parameters and modified deep transfer learning
Yeganeh Modaresnia, Farhad Abedinzadeh Torghabeh, Seyyed Abed Hosseini
Multimedia Tools and Applications (2024) Vol. 83, Iss. 34, pp. 81455-81476
Closed Access | Times Cited: 2
Self-supervised approach for diabetic retinopathy severity detection using vision transformer
Kriti Ohri, Mukesh Kumar, Deepak Sukheja
Progress in Artificial Intelligence (2024) Vol. 13, Iss. 3, pp. 165-183
Closed Access | Times Cited: 1
Domain and label efficient approach for diabetic retinopathy severity detection
Kriti Ohri, Mukesh Kumar
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 35795-35824
Closed Access | Times Cited: 2
Transfer Learning Approach for Classification of Diabetic Retinopathy using Fine-Tuned ResNet50 Deep Learning Model
Srilaxmi Dasari, Boo. Poonguzhali, Manjula Sri Rayudu
(2023), pp. 1361-1367
Closed Access | Times Cited: 1
Diabetic Retinopathy Prediction Based on a Hybrid Deep Learning Approach
Mohammed Oulhadj, Jamal Riffi, Chaimae Khodriss, et al.
(2024), pp. 1-5
Closed Access
OMSF2: optimizing multi-scale feature fusion learning for pneumoconiosis staging diagnosis through data specificity augmentation
Xueting Ren, Surong Chu, Guohua Ji, et al.
Complex & Intelligent Systems (2024) Vol. 11, Iss. 1
Open Access
Diabetic Retinopathy Segmentation and Classification Using U-Net with Convolutional Neural Network
Ghazi Mohamad Ramadan, Myasar Mundher Adnan, Zamen Latef Naser, et al.
(2023), pp. 1-5
Closed Access
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