CNN Classification of the Cultural Heritage Images

被引:8
|
作者
Cosovic, Marijana [1 ]
Jankovic, Radmila [2 ]
机构
[1] Univ East Sarajevo, Fac Elect Engn, East Sarajevo, Bosnia & Herceg
[2] Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia
来源
2020 19TH INTERNATIONAL SYMPOSIUM INFOTEH-JAHORINA (INFOTEH) | 2020年
关键词
cultural heritage; image classification; machine learning; deep neural networks;
D O I
10.1109/infoteh48170.2020.9066300
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The cultural heritage image classification represents one of the most important tasks in the process of digitalization. In this paper, a deep learning neural network was applied in order to classify images of architectural heritage belonging to ten categories, in particular: (i) bell tower, (ii) stained glass, (iii) vault, (iv) column, (v) outer dome, (vi) altar, (vii) apse, (viii) inner dome, (ix) flying buttress, and (x) gargoyle. The Convolutional neural network was used for image classification, with the same architecture applied on two sets of the data: the full dataset consisting of 10 categories as well as dataset with 5 different image categories. The results show that both architectures performed well and obtained accuracy of up to 90%.
引用
收藏
页数:6
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