Application of hyperspectral imaging and chemometric calibrations for variety discrimination of maize seeds

Sensors (Switzerland)

Volumn 12, Issue 12, 2012, Pages 17234-17246

  Zhang, Xiaolei ^a   Liu, Fei ^a   He, Yong ^a,b,c   Li, Xiaoli ^a,b,c  

^a ZHEJIANG UNIVERSITY   (China)

^b ZHEJIANG UNIVERSITY   (China)

^c BEIJING HOSPITAL   (China)

Author keywords

Back propagation neural network; Gray level co occurrence; Hyperspectral imaging; Kernel principal component analysis; Least squares support vector machine; Maize seed; Principal component analysis; Variety identification

Indexed keywords

BACK PROPAGATION NEURAL NETWORKS; CO-OCCURRENCE; HYPERSPECTRAL IMAGING; KERNEL PRINCIPAL COMPONENT ANALYSES (KPCA); LEAST SQUARES SUPPORT VECTOR MACHINES; MAIZE SEEDS; VARIETY IDENTIFICATION;

NEURAL NETWORKS; OPTIMIZATION; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

PRINCIPAL COMPONENT ANALYSIS;

ARTICLE; IMAGE PROCESSING; LIGHT; MAIZE; NEAR INFRARED SPECTROSCOPY; PLANT SEED; PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR MACHINE;

IMAGE PROCESSING, COMPUTER-ASSISTED; LIGHT; PRINCIPAL COMPONENT ANALYSIS; SEEDS; SPECTROSCOPY, NEAR-INFRARED; SUPPORT VECTOR MACHINES; ZEA MAYS;

EID: 84871705963     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s121217234     Document Type: Article

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