Open Access Helper

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:

Dual branch deep learning network for detection and stage grading of diabetic retinopathy
Hossein Shakibania, Sina Raoufi, Behnam Pourafkham, et al.
Biomedical Signal Processing and Control (2024) Vol. 93, pp. 106168-106168
Open Access | Times Cited: 8

Showing 8 citing articles:

A deep learning based model for diabetic retinopathy grading
Samia Akhtar, Shabib Aftab, Omar Farouk, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open 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
Advancing diabetic retinopathy classification using ensemble deep learning approaches
Ankur Biswas, Rita Banik
Biomedical Signal Processing and Control (2025) Vol. 106, pp. 107804-107804
Closed Access
Two-stage deep learning classification for diabetic retinopathy using gradient weighted class activation mapping
Abderaouf M. Moustari, Youcef Brik, Bilal Attallah, et al.
Automatika (2024) Vol. 65, Iss. 3, pp. 1284-1299
Open Access | Times Cited: 2
Deep learning based binary classification of diabetic retinopathy images using transfer learning approach
Dimple Saproo, Aparna N. Mahajan, Seema Narwal
Journal of Diabetes & Metabolic Disorders (2024) Vol. 23, Iss. 2, pp. 2289-2314
Closed Access | Times Cited: 1
A wavelet CNN with appropriate feed-allocation and PSO optimized activations for diabetic retinopathy grading
C. Raja, Santhosh Krishna B V, L. Balaji, et al.
Automatika (2024) Vol. 65, Iss. 4, pp. 1593-1605
Open Access | Times Cited: 1
Potential Screening, Grading and Follow-Up of Diabetic Retinopathy in Primary Care Using Artificial Intelligence – How Hard Would It Be to Implement? An Ophthalmologist’s Perspective
Alexandra Cristina Rusu, Raluca Ozana Chistol, Simona-Irina Damian, et al.
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE (2024) Vol. 15, Iss. 2, pp. 280-303
Open Access
Enhanced Detection and Segmentation of Retinal Exudates in Diabetic Retinopathy using a Feature Pyramid Network with EfficientNet-B0 Encoder
D Praneeth, N Satheesh Kumar, V. Nagaraju
Indian Journal of Science and Technology (2024) Vol. 17, Iss. 32, pp. 3377-3387
Open Access
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