National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [U1833119, 42074172]; National Food and Strategic Reserves Administration Foundation [LQ2018501]; Hubei province Natural Science Foundation for Distinguished Young Scholars [2020CFA063]
机构署名：
本校为第一机构
院系归属：
电气与电子工程学院
数学与计算机学院
摘要：
Hyperspectral technology is used to obtain spectral and spatial information of samples simultaneously and demonstrates significant potential for use in seed purity identification. However, it has certain limitations, such as high acquisition cost and massive redundant information. This study integrates the advantages of the sparse feature of the least absolute shrinkage and selection operator (LASSO) algorithm and the classification feature of the logistic regression model (LRM). We propose a hyperspectral rice seed purity identification method based on the LASSO logistic regression model (LLR...
