Page 82 - eBook_Proceedings of the International Conference on Digital Manufacturing V2

Proceedings of the International Conference on Digital Manufacturing –
Volume 2

Tan, Xiaoyun, Zhang, Lei, Zhang, Ying, Li, Jie, Yu, Jian, &
Wang, Yan. (2021). Automatic model for cervical cancer
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Kakudi, Halilu A., & Abiodun, John O. (2022). A machine
learning method for classification of cervical cancer.
Electronics, 11(3), 434.
Wang, Jie, Li, Fang, Xu, Qiang, Zhang, Peng, Liu, Wei, & Zhao,
Ming. (2024). Artificial intelligence enables precision
diagnosis of cervical cytology grades and cervical cancer.
Nature Communications, 15(1), Article 574.
Win, Kyaw P., Kitjaidure, Yanin, Hamamoto, Kazuhiko, & Aung,
Thida M. (2020). Computer-assisted screening for cervical
cancer using digital image processing of pap smear images.
Applied Sciences, 10(5), 1710.
Xiang, Yu, Sun, Wei, Pan, Changhao, Yan, Ming, Yin, Zhiqiang,
& Liang, Yujun. (2020). A novel automation-assisted
cervical cancer reading method based on convolutional
neural network. Biocybernetics and Biomedical Engineering,
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Yaman, Onur, & Tuncer, Turker. (2022). Exemplar pyramid deep
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model using pap-smear images. Biomedical Signal
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Zak, Jakub, Grzeszczyk, Mateusz K., Pater, Adam, Roszkowiak,
Lukasz, Siemion, Katarzyna, & Korzynska, Anna. (2022).
Cell image augmentation for classification task using GANs
on Pap smear dataset. Biocybernetics and Biomedical
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