A CNN-LSTM framework for authorship classification of paintings

Kevin Alfianto Jangtjik, Trang Thi Ho, Mei Chen Yeh, Kai Lung Hua

研究成果: 書貢獻/報告類型會議論文篇章

6 引文 斯高帕斯(Scopus)

摘要

The authenticity of digital painting image is an urgent demand in the field of art. Yet, determining the authorship of a certain painting is a challenging task due to two reasons: (1) various artists might share similar painting styles; and (2) an artist could create different styles. In this paper, we present a novel method for authorship classification of paintings based on a CNN-LSTM framework. First, a multiscale pyramid is constructed from a painting image. Second, a CNN-LSTM model is learned and it returns possibly multiple labels for one image. To aggregate the final classification result, an adaptive fusion method is employed. Experimental results show that the proposed method has superior classification performance compared with the state-of-the-art techniques.

原文英語
主出版物標題2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
發行者IEEE Computer Society
頁面2866-2870
頁數5
ISBN(電子)9781509021758
DOIs
出版狀態已發佈 - 2018 二月 20
事件24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, 中国
持續時間: 2017 九月 172017 九月 20

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
2017-September
ISSN(列印)1522-4880

其他

其他24th IEEE International Conference on Image Processing, ICIP 2017
國家中国
城市Beijing
期間2017/09/172017/09/20

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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