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语境聚合器:在联合学习中,一种损失和类不平衡意识聚合的方法

Qamar Abbas1, Khalid Mahmood Malik2, Abdul Khader Jilani Saudagar3

  • 1Department of Computer Science, Faculty of Computing and Information Technology, International Islamic University, Islamabad, 44000, Pakistan.

Computers in biology and medicine
|July 8, 2023
PubMed
概括

医疗成像的联合学习 (FL) 模型可以通过计算每个医院的数据质量和类平衡来改进. 本研究引入了上下文聚合器 (CAVL和CACI),以提高FL模型的性能,特别是用于COVID-19分类.

关键词:
放大加权聚合器放大加权聚合器阶级不平衡造成的不平衡意识到背景,意识到背景.这就是Covid-19的原因.联邦学习学习 (Federated Learning) 是一种学习方式.医学图像分类 医学图像分类验证损失是指验证损失.

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