Identification of Traditional Motifs using Convolutional Neural Networks

被引：0
|
作者：
Jurj, Sorin Liviu [1 ]
Opritoiu, Flavius [1 ]
Vladutiu, Mircea [1 ]
机构：
[1] Politehn Univ Timisoara, Adv Comp Syst & Architectures ACSA Lab, Comp Sci & Engn Dept, 2 V Parvan Blvd, Timisoara 300223, Romania
来源：
2018 IEEE 24TH INTERNATIONAL SYMPOSIUM FOR DESIGN AND TECHNOLOGY IN ELECTRONIC PACKAGING (SIITME) | 2018年
关键词：
Deep Learning; Convolutional Neural Networks; Traditional Motifs; ResNet-50;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents a design for identifying and classifying the Romanian traditional motifs found on 4 different categories (clothes, ceramics, carpets and painted eggs) by training a Convolutional Neural Network (CNN) model derived from the Residual Network (ResNet-50) architecture. We also implemented a system which can detect and identify through a webcam if the object in front of it contains a learned motif. Experimental results show that our neural network has an overall accuracy of 99.4% and a reduced webcam processing time.
引用
收藏
页码：191 / 196
页数：6
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