Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/6881
Title: | In Embedded Systems Image Classification with Convolutional Neural Network | Authors: | Çalık, Rasim Caner Demirci, Muhammed Fatih |
Keywords: | Convolutional Neural Network Deep Neural Network Machine Learning Image Classification |
Publisher: | IEEE | Source: | 26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY | Series/Report no.: | Signal Processing and Communications Applications Conference | Abstract: | Deep Neural Network is successfully applied for image classification problems. The understanding of what object is detected in the image is great interested. The prupose of this article is that image classification problem could be applied in real time systems. In this article we propose a CNN architecture for Cifar-10 dataset. This article is shown that with 2GB memory real time system achieves %85.8 accuracy for image classification. | URI: | https://hdl.handle.net/20.500.11851/6881 | ISBN: | 978-1-5386-1501-0 | ISSN: | 2165-0608 |
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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