Machine learning and computer vision system for phenotype data acquisition and analysis in plants

Sensors (Switzerland)

Volumn 16, Issue 5, 2016, Pages

  Navarro, Pedro J ^a   Pérez, Fernando ^a   Weiss, Julia ^a   Egea Cortines, Marcos ^a  

^a TECHNICAL UNIVERSITY OF CARTAGENA   (Spain)

Author keywords

Circadian clock; Computer vision; Data normalisation; Image segmentation; Machine learning

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLASSIFIERS; COMPUTER VISION; DATA ACQUISITION; DATA HANDLING; IMAGE ACQUISITION; IMAGE SEGMENTATION; INFORMATION ANALYSIS; INFRARED DEVICES; LEARNING SYSTEMS; NEAREST NEIGHBOR SEARCH; SUPPORT VECTOR MACHINES;

CIRCADIAN CLOCK; COMPUTER VISION SYSTEM; GROWTH CHAMBER; K NEAREST NEIGHBOURS (K-NN); KERNEL FUNCTION; NAIVE BAYES CLASSIFIERS; NORMALISATION; PLANT MATERIAL;

LEARNING ALGORITHMS;

ALGORITHM; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; PHENOTYPE; PLANT; SUPPORT VECTOR MACHINE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; PHENOTYPE; PLANTS; SUPPORT VECTOR MACHINE;

EID: 84965017167     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s16050641     Document Type: Article

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