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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:

Retinal Blood Vessels and Optic Disc Segmentation Using U-Net
S. Alex David, C. Mahesh, V. Dhilip Kumar, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 23

Showing 23 citing articles:

UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias
Jasjit S. Suri, Mrinalini Bhagawati, Sushant Agarwal, et al.
IEEE Access (2022) Vol. 11, pp. 595-645
Open Access | Times Cited: 47
Dual-channel asymmetric convolutional neural network for an efficient retinal blood vessel segmentation in eye fundus images
Yanan Xu, Yingle Fan
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 2, pp. 695-706
Closed Access | Times Cited: 28
VisionDeep-AI: Deep learning-based retinal blood vessels segmentation and multi-class classification framework for eye diagnosis
Rakesh Chandra Joshi, Anuj Kumar Sharma, Malay Kishore Dutta
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106273-106273
Closed Access | Times Cited: 7
Improved Brain Tumor Segmentation Using UNet-LSTM Architecture
S. Saran Raj, K Logeshwaran, Anisha Devi Kalluri, et al.
SN Computer Science (2024) Vol. 5, Iss. 5
Closed Access | Times Cited: 5
Enhanced segmentation of optic disc and cup using attention-based U-Net with dense dilated series convolutions
G. Bharadwaja Kumar, Soham Kumar
Neural Computing and Applications (2025)
Closed Access
HUnet: An Efficient Method for Vein Mask Extraction Based on Hierarchical Feature Fusion
Peng Liu, Yujiao Jia, Xiaofan Cao
Symmetry (2025) Vol. 17, Iss. 3, pp. 420-420
Open Access
A comprehensive review of optic disc segmentation methods in adult and pediatric retinal images: from conventional methods to artificial intelligence (CR-ODSeg-AP-CM2AI)
Avinash Bansal, Jan Kubíček, Marek Penhaker, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access
Segmentation of diabetic retinopathy images using deep feature fused residual with U-Net
Meshal Alharbi, Deepak Gupta
Alexandria Engineering Journal (2023) Vol. 83, pp. 307-325
Open Access | Times Cited: 7
Segmentation of Retinal Blood Vessels Using U-Net++ Architecture and Disease Prediction
Manizheh Safarkhani Gargari, MirHojjat Seyedi, Mehdi Alilou
Electronics (2022) Vol. 11, Iss. 21, pp. 3516-3516
Open Access | Times Cited: 10
End-to-End Automatic Classification of Retinal Vessel Based on Generative Adversarial Networks with Improved U-Net
Jieni Zhang, Kun Yang, Zhufu Shen, et al.
Diagnostics (2023) Vol. 13, Iss. 6, pp. 1148-1148
Open Access | Times Cited: 4
Survey on retinal vessel segmentation
Arunakranthi Godishala, Veena Raj, Daphne Teck Ching Lai, et al.
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 1
Spatial attention U-Net model with Harris hawks optimization for retinal blood vessel and optic disc segmentation in fundus images
Puranam Revanth Kumar, B. Shilpa, Rajesh Kumar Jha, et al.
International Ophthalmology (2024) Vol. 44, Iss. 1
Closed Access | Times Cited: 1
Insights into Diabetes Prediction: A Multi-Algorithm Machine Learning Analysis
V. Usha, N. R. Rajalakshmi
(2023), pp. 1207-1212
Closed Access | Times Cited: 2
SIMD implementation of deep CNNs for myopia detection on a single-board computer system
Mamoon A Al Jbaar, Shefa A. Dawwd
Eastern-European Journal of Enterprise Technologies (2023) Vol. 5, Iss. 9 (125), pp. 98-108
Open Access | Times Cited: 2
Grape Leaf Disease Classification Combined with U-Net++ Network and Threshold Segmentation
Guowei Wang, Jiawei Wang, Jiaxin Wang, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 4
Exploring Deep Neural Networks for Accurate Diabetic Retinopathy Prediction
T. Kujani, P. Arivubrakan, Kota Solomon Raju, et al.
2022 International Conference on Communication, Computing and Internet of Things (IC3IoT) (2024) Vol. 8, pp. 1-6
Closed Access
Multiresolution cascaded attention U-Net for localization and segmentation of optic disc and fovea in fundus images
Rajaram Shalini, Varun P. Gopi
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
A Rapid Finger Vein Recognition Approach Based on UNet++
Peng Liu, Yujiao Jia, Xiaofan Cao, et al.
Communications in computer and information science (2024), pp. 76-85
Closed Access
Segmentation of Retinal Blood Vessels and Optic Disc Using Deep Neural Networks: State-Of-The-Art Review
Saba Sheiba, M. Neelakantappa, Amjan Shaik
Studies in systems, decision and control (2024), pp. 139-152
Closed Access
Deep Learning Techniques Advancements in Apple Leaf Disease Detection
E. Kannan, Carmel Mary Belinda M J, S. Alex David, et al.
Procedia Computer Science (2024) Vol. 235, pp. 713-722
Open Access
Retinal Blood Vessel Segmentation Using an EDADCN Architecture—Encoder–Decoder Architecture with Dilated Convolutions and Attention Mechanism
M. J. Carmel Mary Belinda, S. Alex David, E. Kannan, et al.
Lecture notes in networks and systems (2023), pp. 599-613
Closed Access | Times Cited: 1
Development and Validation of Artery-Vein Ratio Measurement Based on Deep Learning Architectures
Maninder Singh, Rajeev Kumar Gupta, Basant Kumar, et al.
TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) (2023), pp. 1-6
Closed Access
Exploring the Impact of Preprocessing Techniques on Retinal Blood Vessel Segmentation Using a Study Group Learning Scheme
Shariq Bashir, Kinza Rohail, Ferhat Sadak, et al.
(2023), pp. 1-6
Open Access
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