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Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

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第一作者： Wen,Chen

第一单位： State Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science and Technology, Wuhan 430074, China.

作者： Wen,Chen ^[1] ; Weiming,Shen ^[1] ; Liang,Gao ^[1] ; Xinyu,Li ^[1]

作者单位： State Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science and Technology, Wuhan 430074, China. ^[1]

关键词 cervical cancer diagnosis deep learning hybrid loss function lightweight convolutional neural networks medical imaging

医学主题词人工智能(Artificial Intelligence);自动化(Automation);癌症早期检测(Early Detection of Cancer);女(雌)性(Female);人类(Humans);宫颈肿瘤(Uterine Cervical Neoplasms)

DOI 10.3390/s22093272

PMID 35590961

发布时间 2022-07-16

基金项目

2021GCRC058/Fundamental Research Funds for the Central Universities of China

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Sensors (Basel, Switzerland)

2022年22卷9期

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Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

Sensors (Basel, Switzerland)

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Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

Sensors (Basel, Switzerland)

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Sensors (Basel, Switzerland)

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