Parking space occupancy detection using deep learning methods;

dc.authorscopusid57203166829
dc.authorscopusid16637174900
dc.contributor.authorKarakaya, Kasım Murat
dc.contributor.authorKarakaya,M.
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-07-05T15:45:11Z
dc.date.available2024-07-05T15:45:11Z
dc.date.issued2018
dc.departmentAtılım Universityen_US
dc.department-tempAkinci F.C., Bilgisayar Mühendisliǧi, Atilim Üniversitesi, Ankara, 06836, Turkey; Karakaya M., Bilgisayar Mühendisliǧi, Atilim Üniversitesi, Ankara, 06836, Turkeyen_US
dc.descriptionAselsan; et al.; Huawei; IEEE Signal Processing Society; IEEE Turkey Section; Netasen_US
dc.description.abstractThis paper presents an approach for gathering information about the availabilty of the parking lots using Convoltional Neural Network (CNN) for image processing running on an embedded system. By using an eflicent neural network model, we made it possible to use a very low cost embedded system compared to the ones used in previous works on this topic. This efficient model's performance is compared to one of the models that proved its accuracy in image classification competitions. In these tests, we used datasets that has thousands of different images taken from parking lots in different light and weather conditions. © 2018 IEEE.en_US
dc.identifier.citation7
dc.identifier.doi10.1109/SIU.2018.8404749
dc.identifier.endpage4en_US
dc.identifier.isbn978-153861501-0
dc.identifier.scopus2-s2.0-85050821244
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2018.8404749
dc.identifier.urihttps://hdl.handle.net/20.500.14411/3866
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- Izmir -- 137780en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectComputer Visionen_US
dc.subjectConvolutional Neural Networksen_US
dc.subjectDeep Learningen_US
dc.subjectSmart Citiesen_US
dc.titleParking space occupancy detection using deep learning methods;en_US
dc.title.alternativeAraç park yerlerinin doluluk durumlarinin derin öǧrenme yöntemi ile tespit edilmesien_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublication93f27ee1-19eb-42dc-b4eb-a3cc7dc4b057
relation.isAuthorOfPublication.latestForDiscovery93f27ee1-19eb-42dc-b4eb-a3cc7dc4b057
relation.isOrgUnitOfPublicatione0809e2c-77a7-4f04-9cb0-4bccec9395fa
relation.isOrgUnitOfPublication.latestForDiscoverye0809e2c-77a7-4f04-9cb0-4bccec9395fa

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