Turcoins: Turkish Republic Coin Dataset

dc.contributor.author Gökberk, Berk
dc.contributor.author Akarun, Lale
dc.contributor.author Temiz, Hüseyin
dc.date.accessioned 2021-08-24T10:43:13Z
dc.date.available 2021-08-24T10:43:13Z
dc.date.issued 2021
dc.description.abstract In this paper, we present a novel and comprehensive dataset which contains Turkish Republic coins minted since 1924 and present a deep learning based system that can automatically classify coins. The proposed dataset consists of 11080 coin images from 138 different classes. To classify coins, we utilize a pre-trained neural network (ResNet50) which is pre-trained on ImageNet. We train the pre-trained neural networks on our dataset by transfer learning. The imbalanced nature of the dataset causes the classifier to show lower performance in classes with fewer samples. To alleviate the imbalance problem, we propose a StyleGAN2-based augmentation method providing realisticfake coins for rare classes. The dataset will be published in http://turcoins.
dc.identifier.citation Temiz, H., Gökberk, B., & Akarun, L. (9-11 June 2021). TurCoins: Turkish Republic Coin Dataset. In 2021 29th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). https://doi.org/10.1109/SIU53274.2021.9477957
dc.identifier.doi 10.1109/SIU53274.2021.9477957
dc.identifier.issn 9781665436496
dc.identifier.scopus 2-s2.0-85111419467
dc.identifier.uri https://doi.org/10.1109/SIU53274.2021.9477957
dc.identifier.uri https://hdl.handle.net/20.500.11779/1546
dc.language.iso en
dc.publisher IEEE
dc.relation.ispartof 2021 29th Signal Processing and Communications Applications Conference (SIU)
dc.rights info:eu-repo/semantics/closedAccess
dc.subject Art
dc.subject Signal processing
dc.subject Transfer learning
dc.subject Support vector machines
dc.subject Residual neural networks
dc.subject Barium , neural networks
dc.title Turcoins: Turkish Republic Coin Dataset
dc.title.alternative TurCoins: Türkiye cumhuriyeti madeni para veri kümesi
dc.type Conference Object
dspace.entity.type Publication
gdc.author.id Berk Gökberk / 0000-0001-6299-1610
gdc.author.institutional Gökberk, Berk
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gdc.coar.access metadata only access
gdc.coar.type text::conference output
gdc.description.department Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
gdc.description.endpage 4
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
gdc.description.startpage 1-4
gdc.description.woscitationindex Conference Proceedings Citation Index - Science
gdc.identifier.openalex W3185581175
gdc.identifier.wos WOS:000808100700198
gdc.index.type WoS
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gdc.oaire.influence 3.1877345E-9
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gdc.oaire.popularity 4.8747237E-9
gdc.oaire.publicfunded false
gdc.openalex.fwci 0.30665844
gdc.openalex.normalizedpercentile 0.55
gdc.opencitations.count 3
gdc.plumx.crossrefcites 1
gdc.plumx.mendeley 2
gdc.plumx.scopuscites 2
gdc.publishedmonth Haziran
gdc.relation.journal SIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedings
gdc.scopus.citedcount 2
gdc.virtual.author Gökberk, Berk
gdc.wos.citedcount 0
gdc.wos.collaboration Uluslararası işbirliği ile yapılmayan - HAYIR
gdc.wos.documenttype Proceedings Paper
gdc.wos.indexdate 2022
gdc.wos.publishedmonth Haziran
gdc.yokperiod YÖK - 2020-21
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