Publicación:
Implications of Very Deep Super-Resolution (VDSR) on RGB imagery for grain yield assessment in wheat

dc.contributor.authorFernandez-Gallego, Jose A.
dc.contributor.authorKefauver, Shawn C.
dc.contributor.authorGutiérrez, Nieves A.
dc.date.accessioned2022-03-30T16:36:44Z
dc.date.available2022-03-30T16:36:44Z
dc.date.issued2021-09-13
dc.description.abstractRGB imagery has been widely used for crop management practices and phenotyping applications in recent years. Although RGB wavelengths (400-700 nm) are not able to capture all essential plant data (such as with full ultraviolet, near and long infrared wavelength coverage), RGB cameras are the most common types of cameras and are among the versatile imaging devices for proximal remote sensing applications. Deep learning strategies have improved a wide range of processes and deep learning concepts can be included in many applications. This work uses the Very Deep Super-Resolution (VDSP) technique to improve low-resolution RGB images in order to study grain yield assessment in wheat using vegetation indexes. The results show no significant differences between indexes calculated from low-resolution images and low-resolution images processed using VDSP with grain yield.es_CO
dc.description.sponsorshipUniversidad de Ibaguées_CO
dc.identifier.citationJ. A. Fernandez-Gallego, S. C. Kefauver, N. A. Gutiérrez, M. T. Nieto-Taladriz and J. L. Araus, "Implications of Very Deep Super-Resolution (VDSR) on RGB imagery for grain yield assessment in wheat," 2020 Virtual Symposium in Plant Omics Sciences (OMICAS), 2020, pp. 1-5, doi: 10.1109/OMICAS52284.2020.9535654.es_CO
dc.identifier.isbn978-1-6654-3331-0
dc.identifier.urihttps://ieeexplore.ieee.org/document/9535654/authors
dc.language.isoenes_CO
dc.publisher2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020es_CO
dc.subjectDeep learninges_CO
dc.subjectSuper resolutiones_CO
dc.subjectVegetation mappinges_CO
dc.subjectCropses_CO
dc.subjectCamerases_CO
dc.subjectIndexeses_CO
dc.subjectRemote sensinges_CO
dc.titleImplications of Very Deep Super-Resolution (VDSR) on RGB imagery for grain yield assessment in wheates_CO
dc.typeArticlees_CO
dspace.entity.typePublication
eperson.emailjose.fernandez@unibague.edu.coes_CO
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