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Use of artificial neural networks in the identification and classification of tomatoes
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2013
Year
Artificial IntelligencePrecision AgricultureEngineeringMachine LearningNeural NetworkAgricultural EconomicsIntelligent SystemsYield PredictionAgricultural CyberneticsImage AnalysisPattern RecognitionComputer Image AnalysisOptical Image RecognitionFood QualityApplied Artificial IntelligenceAutomated InspectionComputer VisionAgricultural EngineeringArtificial Neural Networks
The project aimed to produce a classification model of neural network that would allow automatic evaluate quality of greenhouse tomatoes. The project used computer image analysis and artificial neural networks. Authors based on the analysis of biological material selected set of features that are describing the physical parameters allowing the quality class identification. Image analysis of tomatoes digital photographs samples allowed to choose characteristics features. Obtained characteristics from the images were used as learning data for artificial neural network.