$Image 1_Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning.tif$

Image 1_Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning.tif

<p>Chlorophyll density (ChD) can reflect the photosynthetic capacity of the winter wheat population, therefore achieving real-time non-destructive monitoring of ChD in winter wheat is of great significance for evaluating the growth status of winter wheat. Derivative preprocessing has a wide ra...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Chenbo Yang (10004575) (author)
مؤلفون آخرون:	Meichen Feng (3621626) (author), Juan Bai (798838) (author), Hui Sun (107933) (author), Rutian Bi (12501683) (author), Lifang Song (10222278) (author), Chao Wang (146527) (author), Yu Zhao (104852) (author), Wude Yang (3621620) (author), Lujie Xiao (3621623) (author), Meijun Zhang (10790996) (author), Xiaoyan Song (2887361) (author)
منشور في:	2025
الموضوعات:	Plant Biology hyperspectral chlorophyll density fractional-order derivative competitive adaptive reweighted sampling machine learning
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

Image 1_Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning.tif

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