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dc.contributor.authorChicchón Apaza, Miguel Ángel
dc.contributor.authorHuerta, Ronny
dc.contributor.otherChicchón Apaza, Miguel Ángel
dc.date.accessioned2021-08-23T14:55:34Z
dc.date.available2021-08-23T14:55:34Z
dc.date.issued2021
dc.identifier.citationChicchón M. & Huerta R. (2021). Semantic Segmentation Using Convolutional Neural Networks for Volume Estimation of Native Potatoes at High Speed. In: Lossio-Ventura J.A., Valverde-Rebaza J.C., Díaz E., Alatrista-Salas H. (eds.) Information Management and Big Data: Seventh Annual International Conference, SIMBig 2020, Lima, Perú, October 1–3, 2020, Proceedings, Communications in Computer and Information Science (vol.1410, pp. 236-249). Springer. https://doi.org/10.1007/978-3-030-76228-5_17es_PE
dc.identifier.issn1865-0929
dc.identifier.urihttps://hdl.handle.net/20.500.12724/13906
dc.descriptionIndexado en Scopuses_PE
dc.description.abstractPeru is one of the main producers of a wide variety of native potatoes in the world. Nevertheless, to achieve a competitive export of derived products is necessary to implement automation tasks in the production process. Nowadays, volume measurements of native potatoes are done manually, increasing production costs. To reduce these costs, a deep approach based on convolutional neural networks have been developed, tested, and evaluated, using a portable machine vision system to improve high-speed native potato volume estimations. The system was tested under different conditions and was able to detect volume with up to 90% of accuracy.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherSpringeres_PE
dc.relation.ispartofurn:issn:1865-0929
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceRepositorio Institucional - Ulimaes_PE
dc.sourceUniversidad de Limaes_PE
dc.subjectPapas (tubérculos)es_PE
dc.subjectProducción eficientees_PE
dc.subjectIndustria alimentariaes_PE
dc.subjectPotatoeses_PE
dc.subjectLean manufacturinges_PE
dc.subjectFood industry and tradees_PE
dc.subject.classificationIngeniería industrial / Producciónes_PE
dc.titleSemantic Segmentation Using Convolutional Neural Networks for Volume Estimation of Native Potatoes at High Speedes_PE
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.otherArtículo de conferencia en Scopuses_PE
ulima.areas.lineasdeinvestigacionProductividad y empleo / Innovación: tecnologías y productoses_PE
dc.identifier.journalCommunications in Computer and Information Sciencees_PE
dc.publisher.countryDEes_PE
dc.description.peer-reviewRevisión por pareses_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.00
dc.identifier.doihttps://doi.org/10.1007/978-3-030-76228-5_17
dc.type.versioninfo:eu-repo/semantics/publishedVersion
ulima.autor.afiliacionChicchón, Miguel (Exponential Technology Group (GITX-ULIMA), Institute of Scientific Research (IDIC), University of Lima)es_PE
ulima.autor.carreraNo figura en la lista del año 2021es_PE
dc.identifier.isni0000000121541816


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