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:

ACCPG-Net: A skin lesion segmentation network with Adaptive Channel-Context-Aware Pyramid Attention and Global Feature Fusion
Wenyu Zhang, Fuxiang Lu, Wei Zhao, et al.
Computers in Biology and Medicine (2023) Vol. 154, pp. 106580-106580
Closed Access | Times Cited: 17

Showing 17 citing articles:

LeaNet: Lightweight U-shaped architecture for high-performance skin cancer image segmentation
Binbin Hu, Pan Zhou, Hongfang Yu, et al.
Computers in Biology and Medicine (2024) Vol. 169, pp. 107919-107919
Closed Access | Times Cited: 27

FDUM-Net: An enhanced FPN and U-Net architecture for skin lesion segmentation
H. Sharen, Malathy Jawahar, L. Jani Anbarasi, et al.
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 106037-106037
Closed Access | Times Cited: 9

RA-Net: Region-Aware Attention Network for Skin Lesion Segmentation
Asim Naveed, Syed S. Naqvi, Shahzaib Iqbal, et al.
Cognitive Computation (2024) Vol. 16, Iss. 5, pp. 2279-2296
Closed Access | Times Cited: 5

OCCMNet: Occlusion-Aware Class Characteristic Mining Network for multi-class artifacts detection in endoscopy
Chenchu Xu, Yu Chen, Jie Liu, et al.
Medical & Biological Engineering & Computing (2025)
Closed Access

Hybrid 3D U-Net and Attention Mechanisms for Whole Heart Segmentation from CT Images
A.N.T.J. Kotte, V. Kamakshi Prasad
Engineering Technology & Applied Science Research (2025) Vol. 15, Iss. 2, pp. 21822-21828
Open Access

MSGAT: Multi-scale gated axial reverse attention transformer network for medical image segmentation
Y.Q. Liu, Haijiao Yun, Yang Xia, et al.
Biomedical Signal Processing and Control (2024) Vol. 95, pp. 106341-106341
Closed Access | Times Cited: 3

TransLevelSet: Integrating Vision Transformers with Level-Sets for Medical Image Segmentation
Dimitra-Christina C. Koutsiou, Michalis A. Savelonas, Dimitris K. Iakovidis
Neurocomputing (2024) Vol. 599, pp. 128077-128077
Closed Access | Times Cited: 1

MASDF-Net: A Multi-Attention Codec Network with Selective and Dynamic Fusion for Skin Lesion Segmentation
Jinghao Fu, Hongmin Deng
Sensors (2024) Vol. 24, Iss. 16, pp. 5372-5372
Open Access | Times Cited: 1

AD-Net: Attention-based dilated convolutional residual network with guided decoder for robust skin lesion segmentation
Asim Naveed, Syed S. Naqvi, Tariq Khan, et al.
Neural Computing and Applications (2024)
Closed Access | Times Cited: 1

A Bi-directionally Fused Boundary Aware Network for Skin Lesion Segmentation
Feiniu Yuan, Y. Peng, Qinghua Huang, et al.
IEEE Transactions on Image Processing (2024) Vol. 33, pp. 6340-6353
Closed Access | Times Cited: 1

MCGFF-Net: a multi-scale context-aware and global feature fusion network for enhanced polyp and skin lesion segmentation
Yanxiang Li, Wenzhe Meng, Dehua Ma, et al.
The Visual Computer (2024)
Closed Access | Times Cited: 1

Deep Learning in Distance Awareness Using Deep Learning Method
Raghad I. Hussein, Ameer N. Onaizah
Lecture notes in networks and systems (2024), pp. 469-479
Closed Access

Harmonious parameters and performance: Lightweight convolutional stage and local feature weighted fusion MLP for medical image segmentation
Y. Chen, Yu-Jie Xiong, Xiaopeng Qiu, et al.
Biomedical Signal Processing and Control (2024) Vol. 98, pp. 106726-106726
Closed Access

An optimized boosting framework for skin lesion segmentation and classification
Ashok Kumar Yadav, Rajesh Mehta, Vinit Kumar, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 18, pp. 53875-53896
Closed Access | Times Cited: 1

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