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CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron.

W. Liu, C. Li, N. Xu, T. Jiang, M. Rahaman, H. Sun, X. Wu, W. Hu, H. Chen, C. Sun, Y. Yao, and M. Grzegorzek. CoRR, (2022)

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Yü-Sün Sun

Hongqing Sun

Guolin Sun

Xianyong Sun

Han Sun

Other publications of authors with the same name

An Application of Transfer Learning and Ensemble Learning Techniques for Cervical Histopathology Image Classification.D. Xue, X. Zhou, C. Li, Y. Yao, M. Rahaman, J. Zhang, H. Chen, J. Zhang, S. Qi, and H. Sun. IEEE Access, (2020)A state-of-the-art survey of U-Net in microscopic image analysis: from simple usage to structure mortification.J. Wu, W. Liu, C. Li, T. Jiang, I. Shariful, Y. Yao, H. Sun, X. Li, X. Li, X. Huang and 1 other author(s). Neural Comput. Appl., 36 (7): 3317-3346 (2024)AATCT-IDS: A Benchmark Abdominal Adipose Tissue CT Image Dataset for Image Denoising, Semantic Segmentation, and Radiomics Evaluation.Z. Ma, C. Li, T. Du, L. Zhang, D. Tang, D. Ma, S. Huang, Y. Liu, Y. Sun, Z. Chen and 4 other author(s). CoRR, (2023)Is Image Size Important? A Robustness Comparison of Deep Learning Methods for Multi-scale Cell Image Classification Tasks: from Convolutional Neural Networks to Visual Transformers.W. Liu, C. Li, H. Sun, W. Hu, H. Chen, C. Sun, and M. Grzegorzek. CoRR, (2021)EBHI-Seg: A Novel Enteroscope Biopsy Histopathological Haematoxylin and Eosin Image Dataset for Image Segmentation Tasks.L. Shi, X. Li, W. Hu, H. Chen, J. Chen, Z. Fan, M. Gao, Y. Jing, G. Lu, D. Ma and 8 other author(s). CoRR, (2022)TOD-CNN: An effective convolutional neural network for tiny object detection in sperm videos.S. Zou, C. Li, H. Sun, P. Xu, J. Zhang, P. Ma, Y. Yao, X. Huang, and M. Grzegorzek. Comput. Biol. Medicine, (2022)PIS-Net: A Novel Pixel Interval Sampling Network for Dense Microorganism Counting in Microscopic Images.J. Zhang, C. Li, H. Sun, and M. Grzegorzek. ITIB, volume 1429 of Advances in Intelligent Systems and Computing, page 307-318. Springer, (2022)Cervical Histopathology Image Classification Using Ensembled Transfer Learning.C. Li, D. Xue, F. Kong, Z. Hu, H. Chen, Y. Yao, H. Sun, L. Zhang, J. Zhang, T. Jiang and 2 other author(s). ITIB, volume 1011 of Advances in Intelligent Systems and Computing, page 26-37. Springer, (2019)CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron.W. Liu, C. Li, N. Xu, T. Jiang, M. Rahaman, H. Sun, X. Wu, W. Hu, H. Chen, C. Sun and 2 other author(s). CoRR, (2022)A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortification.J. Wu, W. Liu, C. Li, T. Jiang, I. Shariful, H. Sun, X. Li, X. Li, X. Huang, and M. Grzegorzek. CoRR, (2022)

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Disambiguation of "Sun, Hongzan"

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CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron.

Please choose a person to relate this publication to

Yü-Sün Sun

Hongqing Sun

Guolin Sun

Xianyong Sun

Han Sun

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Sun, Hongzan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron.

Please choose a person to relate this publication to

Yü-Sün Sun

Hongqing Sun

Guolin Sun

Xianyong Sun

Han Sun

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
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CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron.