Show simple item record

dc.contributor.advisorBeltrán Castañón, César Armando
dc.contributor.authorGonzalez Villarreal, Jessenia Margareth Marina
dc.date.accessioned2020-07-02T23:23:37Z
dc.date.available2020-07-02T23:23:37Z
dc.date.created2020
dc.date.issued2020-07-02es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12404/16610
dc.description.abstractRemote sensing is widely used to monitor earth surfaces with the main objective of extracting information from it. Such is the case of water surface, which is one of the most affected extensions when flood events occur, and its monitoring helps in the analysis of detecting such affected areas, considering that adequately defining water surfaces is one of the biggest problems that Peruvian authorities are concerned with. In this regard, semi automatic mapping methods improve this monitoring, but this process remains a time-consuming task and into the subjectivity of the experts. In this work, we present a new approach for segmenting water surfaces from satellite images based on the application of convolutional neural networks. First, we explore the application of a U-Net model and then a transfer knowledge-based model. Our results show that both approaches are comparable when trained using an 680-labelled satellite image dataset; however, as the number of training samples is reduced, the performance of the transfer knowledge-based model, which combines high and very high image resolution characteristics, is improvedes_ES
dc.description.uriTrabajo de investigaciónes_ES
dc.language.isoenges_ES
dc.publisherPontificia Universidad Católica del Perúes_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.subjectSensores remotoses_ES
dc.subjectReconocimiento de imágeneses_ES
dc.subjectSatélites artificialeses_ES
dc.subjectRedes neuronaleses_ES
dc.titleApplication on semantic segmentation with few labels in the detection of water bodies from PERUSAT-1 satellite's imageses_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
thesis.degree.nameMaestro en Informática con mención en Ciencias de la Computaciónes_ES
thesis.degree.levelMaestríaes_ES
thesis.degree.grantorPontificia Universidad Católica del Perú. Escuela de Posgradoes_ES
thesis.degree.disciplineInformática con mención en Ciencias de la Computaciónes_ES
renati.advisor.dni29561260
renati.advisor.orcidhttps://orcid.org/0000-0002-0173-4140es_ES
renati.discipline611087es_ES
renati.levelhttps://purl.org/pe-repo/renati/level#maestroes_ES
renati.typehttp://purl.org/pe-repo/renati/type#trabajoDeInvestigaciones_ES
dc.publisher.countryPEes_ES
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.00es_ES


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record