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Updated: Sep 9, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
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通过GAF增强特征融合卷积神经网络准确分类多种植西瓜

Changqing An1,2,3, Maozhen Qu1, Yiran Zhao1,2,3

  • 1College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.

Foods (Basel, Switzerland)
|August 28, 2025
PubMed
概括

这项研究引入了一种使用格拉米角场 (GAF) 和卷积神经网络 (CNN) 准确分类西瓜的新方法. 用GAF增强的CNN显著改善了使用VIS-NIR光谱的无种子和种子西瓜的分类.

关键词:
格拉米安角场卷积神经网络功能融合多种植的西瓜波长的选择

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相关概念视频

Aggregates Classification01:29

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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