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使用深度卷积神经网络在超声波图像中对乳腺病变进行分类:转移学习与自动架构设计对比

Alaa AlZoubi1, Feng Lu2, Yicheng Zhu3

  • 1School of Computing and Engineering, University of Derby, Derby, DE22 3AW, UK. a.alzoubi@derby.ac.uk.

Medical & biological engineering & computing
|September 22, 2023
PubMed
概括

一个新的贝叶斯优化设计的卷积神经网络 (BONet) 显示了与转移学习模型相比,超声波图像对乳腺病变的分类精度更高. 突出地图有助于理解BONet的诊断决策.

关键词:
自动架构设计自动架构设计贝叶斯优化的贝叶斯优化乳腺癌是什么? 乳腺癌是什么癌症的识别 癌症的识别深度卷积神经网络是一个深度卷积神经网络.转移学习转移学习超声波学 超声波学 超声波学

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