Varietal quality control in the nursery plant industry using computer vision and deep learning techniques

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Document typeArticle
Defense date2020-01-01
Rights accessOpen Access
Abstract
Computer vision coupled to deep learning is a promising technique withmultiple applications in the industry. In this work, the potential of thistechnique has been assessed in the classification of two varieties of almondtrees (Prunus dulcis), Soleta and Pentacebas. For that, a convolutional neuralnetwork named VGG16 was used. The most appropriate configuration formodel training was studied, which included the comparison between twodifferent filling modes (reflect and nearest) in the data augmentation step, theevaluation of the batch size and the analysis of the image sizes. The robustnessof the model was also checked, and information was obtained about how themodel extracts the information from the images
CitationBorraz, S. [et al.]. Varietal quality control in the nursery plant industry using computer vision and deep learning techniques. "Journal of chemometrics", 1 Gener 2020, vol. Special issue, p. 1-11.
ISSN0886-9383
Collections
- UMA - Unitat de Mecanització Agrària - Articles de revista [40]
- Departament de Teoria del Senyal i Comunicacions - Articles de revista [2.325]
- MVCO - Millora Vegetal de Caràcters Organolèptics - Articles de revista [106]
- Doctorat en Tecnologia Agroalimentària i Biotecnologia - Articles de revista [42]
- Departament d'Enginyeria Agroalimentària i Biotecnologia - Articles de revista [935]
- IMP - Information Modeling and Processing - Articles de revista [47]
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