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Mısır gevreği kesik kulak alanında sayma Zenithal RGB görüntüleri kullanarak koşulları
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Mısır gevreği kesik kulak alanında sayma Zenithal RGB görüntüleri kullanarak koşulları
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11:49 min
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February 02, 2019
DOI:
1Plant Physiology Section, Faculty of Biology,University of Barcelona, 2Agrotecnio, 3Programa de Ingeniería Electrónica, Facultad de Ingeniería,Universidad de Ibagué, 4Instituto Tecnológico Agrario de Castilla y León (ITACyL), 5Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 6Syngenta Spain
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Cereal Ear CountingField ConditionsZenithal RGB ImagesWheat EarsBarley EarsRemote SensingProximal SensingField High-throughput PhenotypingYield ComponentsEar DensityGrain Per EarThousand Kernel WeightAutomatic CountingImage AnalysisCrop Growth StageSatellite ImagesLaplacian Frequency FilterImage SegmentationMachine LearningValidation
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Fernandez-Gallego, J. A., Buchaillot, M. L., Gracia-Romero, A., Vatter, T., Diaz, O. V., Aparicio Gutiérrez, N., Nieto-Taladriz, M. T., Kerfal, S., Serret, M. D., Araus, J. L., Kefauver, S. C. Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images. J. Vis. Exp. (144), e58695, doi:10.3791/58695 (2019).
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