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Updated: Jan 11, 2026

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使用可解释的轻量级CNN通过监督和半监督的自我训练方法实时分类叶病

Meftahul Jannat1, Md Shahab Uddin2, Mohammad Asif Hasan1

  • 1Department of Electronics and Telecommunication Engineering, Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh.

Frontiers in plant science
|November 10, 2025
PubMed
概括

这项研究引入了一种轻量级的深度学习模型,用于使用最小的标记数据检测叶病. 该模型在监督和半监督环境中实现了高精度,为农民提供了实际的解决方案.

关键词:
深度学习是一种深度学习.分组的卷积卷积.果汁叶病是果汁叶病的一种疾病.轻量级的美国有线电视新闻网 (CNN)半监督的自我训练挤压和激发的激发.

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