ICPNet:先进的玉米叶病检测与多维注意力和协调深度卷积

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Updated: Jun 14, 2025

Author Spotlight: Improved Methods for Preparing Transverse Sections and Unrolled Whole Mounts of Maize Leaf Primordia for Fluorescence and Confocal Imaging
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Author Spotlight: Improved Methods for Preparing Transverse Sections and Unrolled Whole Mounts of Maize Leaf Primordia for Fluorescence and Confocal Imaging

Published on: September 22, 2023

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Jin Yang1, Wenke Zhu2, Guanqi Liu1

  • 1College of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha 410004, China.

Plants (Basel, Switzerland)
|August 29, 2024
PubMed
概括

这项研究引入了ICPNet,一种新的玉米疾病检测方法. 它准确地识别出微妙和模糊的疾病特征,提高农业效率和粮食安全.

关键词:
这是一个ICPNet网络.深度学习是一种深度学习.检测玉米叶病的检测方法

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