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

页码：191 / 196

页数：6