Registro sencillo

dc.contributor.authorArana-Arexolaleiba, Nestor
dc.contributor.otherEtxeberria Garcia, Mikel
dc.contributor.otherLabayen, Mikel
dc.contributor.otherZamalloa, Maider
dc.date.accessioned2024-04-30T11:03:22Z
dc.date.available2024-04-30T11:03:22Z
dc.date.issued2020
dc.identifier.isbn978-1-7281-6668-1en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=153942en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/6395
dc.description.abstractThe purpose of this paper is to present the results of the analysis of the application of Deep Learning in the railway domain with a particular focus on a train stop operation. The paper proposes an approach consisting of monocular vision-based and Deep Learning architectures. Even the difficulties imposed by actual regulation, the findings show that Deep Learning architecture can offer promising results in railway localization using techniques like visual odometry, SLAM or pose estimation. Besides, in spite of the many datasets available in the literature needed to train the neural network, none of them have been created for indoor railway environments. Therefore, a new dataset should be created. Furthermore, the paper presents future research and development suggestions for railway applications which contribute to guiding the mid-term research and development.en
dc.language.isoengen
dc.publisherIEEEen
dc.rights© 2020 IEEEen
dc.subjectMachine learningen
dc.subjectRail transportationen
dc.subjectCamerasen
dc.subjectSimultaneous localization and mappingen
dc.subjectVisualizationen
dc.subjectVisual odometryen
dc.titleApplication of Computer Vision and Deep Learning in the railway domain for autonomous train stop operationen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceIEEE/SICE International Symposium on System Integration (SII)en
local.contributor.groupRobótica y automatizaciónes
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.1109/SII46433.2020.9026246en
local.contributor.otherinstitutionhttps://ror.org/03hp1m080es
local.contributor.otherinstitutionhttps://ror.org/000xsnr85es
oaire.format.mimetypeapplication/pdfen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94fen
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(es)

Registro sencillo