Generative adversarial network based data augmentation to improve cervical cell classification model-Reference-Cited by-同舟云学术

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Generative adversarial network based data augmentation to improve cervical cell classification model

Published:2021 Issue:2 Volume:18 Page:1740-1752
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Yu Suxiang, ,Zhang Shuai,Wang Bin,Dun Hua,Xu Long,Huang Xin,Shi Ermin,Feng Xinxing, , , ,

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modelling and Simulation,General Medicine

Reference39 articles.

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2. S. Chen, D. Gao, L. Wang, Y. Zhang, Cervical Cancer Single Cell Image Data Augmentation Using Residual Condition Generative Adversarial Networks, 2020 3rd International Conference on Artificial Intelligence and Big Data (ICAIBD), 2020.

3. D. Xue, X. Zhou, C. Li, Y. Yao, M. M. Rahaman, J. Zhang. et al., An Application of Transfer Learning and Ensemble Learning Techniques for Cervical Histopathology Image Classification, IEEE Access, 8 (2020), 104603–104618.

4. N. Sompawong, J. Mopan, P. Pooprasert, W. Himakhun, K. Suwannarurk, J. Ngamvirojcharoen, et al., Automated pap smear cervical cancer screening using deep learning, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019.

5. M. Wu, C. Yan, H. Liu, Q. Liu, Y. Yin, Automatic classification of cervical cancer from cytological images by using convolutional neural network, Biosci. Rep., 6 (2018), 38.

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2. Classification of cervical cells from the Pap smear image using the RES_DCGAN data augmentation and ResNet50V2 with self-attention architecture;Neural Computing and Applications;2024-09-14

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