Study on the optimal algorithm prediction of corn leaf component information based on hyperspectral imaging

Infrared Physics and Technology

Volumn 78, Issue , 2016, Pages 66-71

  Wu, Qiong ^a,b   Wang, Jihua ^b   Wang, Cheng ^c   Xu, Tongyu ^a  

^a SHENYANG AGRICULTURAL UNIVERSITY   (China)

^b Beijing Research Center for Agrifood Testing and Farmland Monitoring   (China)

^c BEIJING RESEARCH CENTER OF INTELLIGENT EQUIPMENT FOR AGRICULTURE   (China)

Author keywords

Chlorophyll content; Corn seeding; GA; Hyperspectral imaging; PLS

Indexed keywords

ALGORITHMS; GALLIUM; LEAST SQUARES APPROXIMATIONS; NONDESTRUCTIVE EXAMINATION; OPTIMIZATION; REFLECTION; SPECTROSCOPY;

CHARACTERISTIC BANDS; CHLOROPHYLL CONTENTS; HYPERSPECTRAL IMAGING; INFORMATION MODELING; MEASUREMENT ACCURACY; PARTIAL LEAST SQUARE (PLS); QUANTITATIVE MODELING; SPECTRAL CHARACTERISTICS;

GENETIC ALGORITHMS;

EID: 84978962238     PISSN: 13504495     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.infrared.2016.07.011     Document Type: Article

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