Parking space occupancy detection using deep learning methods;
dc.authorscopusid | 57203166829 | |
dc.authorscopusid | 16637174900 | |
dc.contributor.author | Karakaya, Kasım Murat | |
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.citation | 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.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.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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