Identification of high-oil content soybean using hyperspectral reflectance and one-dimensional convolutional neural network
Author:
Affiliation:
1. School of Electrical and Information, Northeast Agricultural University, Harbin, China
Funder
Heilongjiang Provincial Natural Science Foundation
Publisher
Informa UK Limited
Subject
Spectroscopy,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Link
https://www.tandfonline.com/doi/pdf/10.1080/00387010.2022.2160463
Reference40 articles.
1. Establishment of a predictive model to identify suitable soybean genotypes for oil processing
2. Classification and discrimination of soybean (Glycine max (L.) Merr.) genotypes based on their isoflavone content
3. Identification of quantitative trait loci underlying seed oil content of soybean including main, epistatic and QTL×environment effects in different regions of Northeast China
4. Neighborhood mutual information and its application on hyperspectral band selection for classification
5. Computer-vision classification of corn seed varieties using deep convolutional neural network
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