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https://hdl.handle.net/20.500.11851/1959
Title: | Cifar-10 Image Classification With Convolutional Neural Networks for Embedded Systems | Authors: | Çalık, Rasim Caner Demirci, Muhammed Fatih |
Keywords: | Neural network Convolution Convolutional layers |
Publisher: | IEEE | Source: | Çalik, R. C., & Demirci, M. F. (2018, October). Cifar-10 Image Classification with Convolutional Neural Networks for Embedded Systems. In 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA) (pp. 1-2). IEEE. | Series/Report no.: | Proceedings of IEEE/ACS International Conference on Computer Systems and Applications | Abstract: | Convolutional Neural Networks (CNN) have been successfully applied to image classification problems.Although powerful, they require a large amount of memory. The purpose of this paper is to perform image classification using CNNs on the embedded systems, where only a limited amount of memory is available. Our experimental analysis shows that 85.9% image classification accuracy is obtained by our framework while requiring 2GB memory only, making our framework ideal to be used in embedded systems. | Description: | 15th IEEE/ACS International Conference on Computer Systems and Applications (2018 : Aqaba; Jordan) | URI: | https://ieeexplore.ieee.org/document/8612873 https://hdl.handle.net/20.500.11851/1959 |
ISBN: | 978-1-5386-9120-5 | ISSN: | 2161-5322 |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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