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
Issue Date: 2018
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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