Application of neural networks to discriminate fungal infection levels in rice panicles using hyperspectral reflectance and principal components analysis
By Zhanyu Liu, Hongyan Wu, Jingfeng Huang. 2010
135 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Ecology, Plant Science
View Paper: https://www.semanticscholar.org/paper/e54746cd327cee92059372f5a129ec2e16618d85
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In Analytical Chemistry
In Ecology
In Plant Science
Citations in the corpus
- Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages (2014, background): “Derivative analyses of hyperspecral data have been found to be more useful in estimating plant N r pest information in rice than raw reflectance (Kobayashi et al., 001; Liu et al., 2010; Zhang et al., 2011; Huang et al., 2012).”