Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/1546
Title: TurCoins: Turkish republic coin dataset
Other Titles: TurCoins: Türkiye cumhuriyeti madeni para veri kümesi
Authors: Temiz, Hüseyin
Gökberk, Berk
Akarun, Lale
Keywords: Residual neural networks
Barium , Neural networks
Art
Transfer learning
Support vector machines
Signal processing
Publisher: IEEE
Source: 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
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.
URI: https://hdl.handle.net/20.500.11779/1546
https://doi.org/10.1109/SIU53274.2021.9477957
ISSN: 9781665436496
Appears in Collections:Bilgisayar Mühendisliği Bölümü koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File Description SizeFormat 
TurCoins_Turkish_Republic_Coin_Dataset.pdf
  Until 2040-01-01
Proceeding papers2.45 MBAdobe PDFView/Open    Request a copy
Show full item record



CORE Recommender

Page view(s)

4
checked on Jun 26, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.