Publicación:
Mobile Computational Vision System in the Identification of White Quinoa Quality

dc.contributor.authorLecca-Pino, Percimil
dc.contributor.authorTafur-Vera, Daniel
dc.contributor.authorCabanillas-Carbonell, Michael A.
dc.contributor.authorHerrera Salazar, José Luis
dc.contributor.authorMedina-Rafaile, Esteban
dc.date.accessioned2025-09-05T16:38:16Z
dc.description.abstractQuinoa is currently in high commercial demand due to its large benefits and vitamin components. The process of selecting this grain is mostly done manually, being prone to errors, because many times this work is subject to fatigue and to subjective criteria of those in charge, causing the quality to decrease due to not making an adequate selection subject to standards. For this reason, a study focused on determining the influence of the computer vision system for the identification of the quality of white quinoa, based on the standards and techniques for the development of a computer vision system through the phases of PDI. Managing to determine the influence of this, concluding that it is possible to ensure the implementation of robust systems to solve problems by applying computer vision thanks to technological advances for mobile devices © 2021 Elsevier B.V., All rights reserved.
dc.identifier.doi10.14569/IJACSA.2021.0120850
dc.identifier.scopus2-s2.0-85119004621
dc.identifier.urihttps://cris.uwiener.edu.pe/handle/001/1022
dc.identifier.uuidc4e16b18-c7db-47e1-b945-b508c8ffc413
dc.language.isoen
dc.publisherScience and Information Organization
dc.relation.citationissue8
dc.relation.citationvolume12
dc.relation.ispartofseriesInternational Journal of Advanced Computer Science and Applications
dc.relation.issn21565570
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.titleMobile Computational Vision System in the Identification of White Quinoa Quality
dc.typehttp://purl.org/coar/resource_type/c_2df8fbb1
dspace.entity.typePublication
oaire.citation.endPage442
oaire.citation.startPage436

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