Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes

Biosystems Engineering

Volumn 101, Issue 1, 2008, Pages 50-57

  Mahesh, S ^a   Manickavasagan, A ^a   Jayas, D S ^a   Paliwal, J ^a   White, N D G ^b  

^a UNIVERSITY OF MANITOBA   (Canada)

^b Cereal Research Centre   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERICS; BACKPROPAGATION; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DIFFERENTIATION (CALCULUS); DISCRIMINANT ANALYSIS; IMAGE CLASSIFICATION; IMAGING SYSTEMS; IMAGING TECHNIQUES; INFRARED DEVICES; KETONES; LEARNING SYSTEMS; NEURAL NETWORKS; OPTOELECTRONIC DEVICES; SPRINGS (COMPONENTS); STANDARDS; THROUGHPUT;

ANN MODELING; ARTIFICIAL NEURAL NETWORK; BACK-PROPAGATION NEURAL NETWORK; BULK SAMPLES; CHEMICAL COMPOSITIONS; CLASSIFICATION ACCURACIES; CLASSIFICATION MODELS; END PRODUCTS; GRAIN INDUSTRY; HYPER-SPECTRAL IMAGING; HYPERSPECTRAL IMAGING SYSTEMS; LEAVE-ONE-OUT CROSS-VALIDATION; LINEAR DISCRIMINANT ANALYSISLDA); NEAR INFRA-RED; QUADRATIC DISCRIMINANT ANALYSIS; SCANNED IMAGES; STATISTICAL CLASSIFIERS; VALIDATION SETS; WAVELENGTH REGIONS;

GRAIN (AGRICULTURAL PRODUCT);

TRITICUM AESTIVUM;

EID: 50349103029     PISSN: 15375110     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystemseng.2008.05.017     Document Type: Article

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