Parking space occupancy detection using deep learning methods;

dc.authorscopusid 57203166829
dc.authorscopusid 16637174900
dc.contributor.author Akinci,F.C.
dc.contributor.author Karakaya,M.
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T15:45:11Z
dc.date.available 2024-07-05T15:45:11Z
dc.date.issued 2018
dc.department Atılım University en_US
dc.department-temp Akinci F.C., Bilgisayar Mühendisliǧi, Atilim Üniversitesi, Ankara, 06836, Turkey; Karakaya M., Bilgisayar Mühendisliǧi, Atilim Üniversitesi, Ankara, 06836, Turkey en_US
dc.description Aselsan; et al.; Huawei; IEEE Signal Processing Society; IEEE Turkey Section; Netas en_US
dc.description.abstract This 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.citationcount 7
dc.identifier.doi 10.1109/SIU.2018.8404749
dc.identifier.endpage 4 en_US
dc.identifier.isbn 978-153861501-0
dc.identifier.scopus 2-s2.0-85050821244
dc.identifier.startpage 1 en_US
dc.identifier.uri https://doi.org/10.1109/SIU.2018.8404749
dc.identifier.uri https://hdl.handle.net/20.500.14411/3866
dc.institutionauthor Karakaya, Kasım Murat
dc.language.iso tr en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof 26th 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 -- 137780 en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 7
dc.subject Computer Vision en_US
dc.subject Convolutional Neural Networks en_US
dc.subject Deep Learning en_US
dc.subject Smart Cities en_US
dc.title Parking space occupancy detection using deep learning methods; en_US
dc.title.alternative Araç Park Yerlerinin Doluluk Durumlarinin Derin Öǧrenme Yöntemi ile Tespit Edilmesi en_US
dc.type Conference Object en_US
dspace.entity.type Publication
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relation.isAuthorOfPublication.latestForDiscovery 93f27ee1-19eb-42dc-b4eb-a3cc7dc4b057
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relation.isOrgUnitOfPublication.latestForDiscovery e0809e2c-77a7-4f04-9cb0-4bccec9395fa

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