Learning the Principles of Art History with convolutional neural networks-Reference-Cited by-同舟云学术

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Learning the Principles of Art History with convolutional neural networks

Published:2020-01 Issue: Volume:129 Page:56-62
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Cetinic Eva,Lipic Tomislav^ORCID,Grgic Sonja^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference19 articles.

1. Principles of Art History;Wölfflin,1950

2. The shape of art history in the eyes of the machine;Elgammal,2018

3. Recognizing image style;Karayev,2014

4. Classification of artistic styles using binarized features derived from a deep neural network;Bar,2014

5. Deeppainter: painter classification using deep convolutional autoencoders;David,2016

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3. Evolutionary Analysis and Cultural Transmission Models of Color Style Distributions in Painting Arts;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

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