Prediction of the chlorophyll content in pomegranate leaves based on digital image processing technology and stacked sparse autoencoder
Author:
Affiliation:
1. College of Forestry, Nanjing Forestry University, Nanjing, PR China
2. Jiangsu Wiscom Technology Co. Ltd, Nanjing, PR China
Publisher
Informa UK Limited
Subject
Food Science
Link
https://www.tandfonline.com/doi/pdf/10.1080/10942912.2019.1675692
Reference31 articles.
1. Evaluation of chlorophyll meters as tools for N fertilization in winter wheat under humid Mediterranean conditions
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5. Relationships between reflectance and absorbance chlorophyll indices with RGB (Red, Green, Blue) image components in seedlings of tropical tree species at nursery stage
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