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Updated: May 29, 2025

High-Throughput Identification of Resistance to Pseudomonas syringae pv. Tomato in Tomato using Seedling Flood Assay
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一个改进的ShuffleNetV2方法,以集体自蒸为基础,用于番茄叶病的识别

Shuiping Ni1, Yue Jia1, Mingfu Zhu1,2

  • 1School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China.

Frontiers in plant science
|February 5, 2025
PubMed
概括

本研究引入了一种集体自蒸方法,用于使用ShuffleNetV2.2识别轻量级番茄病. 优化的模型在边缘设备上实现了高精度,提高了番茄产量.

关键词:
在ShuffleNetV2中使用.总的来说,一个团队就是一个团队.轻量级的模型轻量级的模型.一个模型的压缩压缩.自蒸自蒸的方法番茄叶病的识别 番茄叶病的识别

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Light Acquisition02:16

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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