Turcoins: Turkish Republic Coin Dataset
dc.authorid | Berk Gökberk / 0000-0001-6299-1610 | |
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.department | Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.description.PublishedMonth | Haziran | en_US |
dc.description.WoSDocumentType | Proceedings Paper | |
dc.description.WoSIndexDate | 2022 | en_US |
dc.description.WoSInternationalCollaboration | Uluslararası işbirliği ile yapılmayan - HAYIR | en_US |
dc.description.WoSPublishedMonth | Haziran | en_US |
dc.description.WoSYOKperiod | YÖK - 2021-22 | en_US |
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. | en_US |
dc.description.woscitationindex | Conference Proceedings Citation Index - Science | en_US |
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 | en_US |
dc.identifier.doi | 10.1109/SIU53274.2021.9477957 | |
dc.identifier.issn | 9781665436496 | |
dc.identifier.scopus | 2-s2.0-85111419467 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.startpage | 1-4 | en_US |
dc.identifier.uri | https://doi.org/10.1109/SIU53274.2021.9477957 | |
dc.identifier.uri | https://hdl.handle.net/20.500.11779/1546 | |
dc.identifier.wos | WOS:000808100700198 | |
dc.identifier.wosquality | N/A | |
dc.institutionauthor | Gökberk, Berk | |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.relation.journal | SIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedings | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Art | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Transfer learning | en_US |
dc.subject | Support vector machines | en_US |
dc.subject | Residual neural networks | en_US |
dc.subject | Barium , neural networks | en_US |
dc.title | Turcoins: Turkish Republic Coin Dataset | en_US |
dc.title.alternative | TurCoins: Türkiye cumhuriyeti madeni para veri kümesi | en_US |
dc.type | Conference Object | en_US |
Files
Original bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- TurCoins_Turkish_Republic_Coin_Dataset.pdf
- Size:
- 2.39 MB
- Format:
- Adobe Portable Document Format
- Description:
- Proceeding papers
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 1.44 KB
- Format:
- Item-specific license agreed upon to submission
- Description: