Parking Space Occupancy Detection Using Deep Learning Methods
dc.authorwosid | KARAKAYA, Murat/A-4952-2013 | |
dc.contributor.author | Akinci, Fatih Can | |
dc.contributor.author | Karakaya, Murat | |
dc.contributor.other | Computer Engineering | |
dc.date.accessioned | 2024-10-06T10:58:20Z | |
dc.date.available | 2024-10-06T10:58:20Z | |
dc.date.issued | 2018 | |
dc.department | Atılım University | en_US |
dc.department-temp | [Akinci, Fatih Can; Karakaya, Murat] Atilim Univ, Bilgisayar Muhendisligi, TR-06836 Ankara, Turkey | 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 efiicent 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. | en_US |
dc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
dc.identifier.citationcount | 0 | |
dc.identifier.isbn | 9781538615010 | |
dc.identifier.issn | 2165-0608 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.uri | https://hdl.handle.net/20.500.14411/8891 | |
dc.identifier.wos | WOS:000511448500602 | |
dc.identifier.wosquality | N/A | |
dc.institutionauthor | Karakaya, Kasım Murat | |
dc.language.iso | tr | en_US |
dc.publisher | Ieee | en_US |
dc.relation.ispartof | 26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY | en_US |
dc.relation.ispartofseries | Signal Processing and Communications Applications Conference | |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Smart Cities | en_US |
dc.subject | Computer Vision | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Convolutional Neural Networks | en_US |
dc.title | Parking Space Occupancy Detection Using Deep Learning Methods | en_US |
dc.type | Conference Object | en_US |
dc.wos.citedbyCount | 0 | |
dspace.entity.type | Publication | |
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