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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