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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:

DGCU–Net: A new dual gradient-color deep convolutional neural network for efficient skin lesion segmentation
Rania Ramadan, Saleh Aly
Biomedical Signal Processing and Control (2022) Vol. 77, pp. 103829-103829
Closed Access | Times Cited: 13

Showing 13 citing articles:

A survey, review, and future trends of skin lesion segmentation and classification
Md. Kamrul Hasan, Md. Asif Ahamad, Choon Hwai Yap, et al.
Computers in Biology and Medicine (2023) Vol. 155, pp. 106624-106624
Open Access | Times Cited: 83
A novel nonlinear automated multi-class skin lesion detection system using soft-attention based convolutional neural networks
Adi Alhudhaif, Bandar Almaslukh, Ahmad O. Aseeri, et al.
Chaos Solitons & Fractals (2023) Vol. 170, pp. 113409-113409
Closed Access | Times Cited: 31
A graph‐based edge attention gate medical image segmentation method
Dechen Hao, Hualing Li
IET Image Processing (2023) Vol. 17, Iss. 7, pp. 2142-2157
Open Access | Times Cited: 11
Segmentation of skin lesion using superpixel guided generative adversarial network with dual-stream patch-based discriminators
Jiahao Zhang, Miao Che, Zongfei Wu, et al.
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106304-106304
Closed Access | Times Cited: 3
ABT-GAMNet: A novel adaptive Boundary-aware transformer with Gated attention mechanism for automated skin lesion segmentation
J. Deepa, P. Madhavan
Biomedical Signal Processing and Control (2023) Vol. 84, pp. 104971-104971
Closed Access | Times Cited: 5
DI-UNet: dual-branch interactive U-Net for skin cancer image segmentation
Wen Yin, Dongming Zhou, Rencan Nie
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 17, pp. 15511-15524
Closed Access | Times Cited: 5
Color-invariant skin lesion semantic segmentation based on modified U-Net deep convolutional neural network
Rania Ramadan, Saleh Aly, Mahmoud Abdel-Atty
Health Information Science and Systems (2022) Vol. 10, Iss. 1
Open Access | Times Cited: 7
Automated Skin Lesion Segmentation using VGG-UNet
Anwar Jimi, Hind Abouche, Nabila Zrira, et al.
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2022), pp. 370-377
Closed Access | Times Cited: 7
TDS-U-Net: Automatic liver and tumor separate segmentation of CT volumes using attention gates1
Hua Wang, Zhiming Wang, Xiu-Tao Cui, et al.
Journal of Intelligent & Fuzzy Systems (2023) Vol. 44, Iss. 6, pp. 8817-8825
Closed Access | Times Cited: 2
Em-Net: Effective and Morphology-Aware Network for Skin Lesion Segmentation
Kaiwen Zhu, Yuezhe Yang, Yonglin Chen, et al.
(2024)
Closed Access
Advancements in Convolutional Neural Networks for Accurate and Efficient Skin Cancer Classification: A Comprehensive Survey
Dattatray G. Takale, Shraddha S. Kashid, Gopal B. Deshmukh, et al.
Lecture notes in networks and systems (2024), pp. 27-45
Closed Access
SegSkin: An Effective Application for Skin Lesion Segmentation Using Attention-Based VGG-UNet
Anwar Jimi, Hind Abouche, Nabila Zrira, et al.
Lecture notes in social networks (2024), pp. 185-210
Closed Access
Hybrid RA2-Net: Residual Atrous Attention Network for Vessel Classification using Fundus Images
Geetha Pavani P, Birendra Biswal, Tapan Kumar Gandhi, et al.
(2023) Vol. 79, pp. 222-227
Closed Access
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