Selection of Optimal Wavelength Features for Decay Detection in Citrus Fruit Using the ROC Curve and Neural Networks

Food and Bioprocess Technology

Volumn 6, Issue 2, 2013, Pages 530-541

  Lorente, Delia ^a   Aleixos, Nuria ^b   Gómez Sanchis, Juan ^c   Cubero, Sergio ^a   Blasco, Jose ^a  

^a INSTITUTO VALENCIANO DE INVESTIGACIONES AGRARIAS IVIA   (Spain)

^b UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^c UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Citrus fruits; Computer vision; Decay; Hyperspectral imaging; Non destructive inspection; ROC curve

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; DECAY (ORGANIC); DIGITAL STORAGE; FEATURE EXTRACTION; HYPERSPECTRAL IMAGING; LEARNING ALGORITHMS; LOSSES; MACHINE LEARNING; MULTILAYER NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; SPECTROSCOPY;

AUTOMATIC DETECTION; DECAY; EXTREME LEARNING MACHINE; MULTICLASS CLASSIFICATION PROBLEMS; NON DESTRUCTIVE INSPECTION; OPTIMAL WAVELENGTH; RECEIVER OPERATING CHARACTERISTIC CURVES; ROC CURVES;

CITRUS FRUITS;

CITRUS;

EID: 84872598205     PISSN: 19355130     EISSN: 19355149     Source Type: Journal    
DOI: 10.1007/s11947-011-0737-x     Document Type: Article

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