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Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning

Starting from a pure-image perspective, using machine learning in emotion analysis methods to study artwork is a new cross-cutting approach in the field of literati painting and is an effective supplement to research conducted from the perspectives of aesthetics, philosophy, and history. This study...

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Autores principales: Zhang, Jie, Duan, Yingjing, Gu, Xiaoqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356227/
https://www.ncbi.nlm.nih.gov/pubmed/34393959
http://dx.doi.org/10.3389/fpsyg.2021.723325
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author Zhang, Jie
Duan, Yingjing
Gu, Xiaoqing
author_facet Zhang, Jie
Duan, Yingjing
Gu, Xiaoqing
author_sort Zhang, Jie
collection PubMed
description Starting from a pure-image perspective, using machine learning in emotion analysis methods to study artwork is a new cross-cutting approach in the field of literati painting and is an effective supplement to research conducted from the perspectives of aesthetics, philosophy, and history. This study constructed a literati painting emotion dataset. Five classic deep learning models were used to test the dataset and select the most suitable model, which was then improved upon for literati painting emotion analysis based on accuracy and model characteristics. The final training accuracy rate of the improved model was 54.17%. This process visualizes the salient feature areas of the picture in machine vision, analyzes the visualization results, and summarizes the connection law between the picture content of the Chinese literati painting and the emotion expressed by the painter. This study validates the possibility of combining deep learning with Chinese cultural research, provides new ideas for the combination of new technology and traditional Chinese literati painting research, and provides a better understanding of the Chinese cultural spirit and advanced factors.
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spelling pubmed-83562272021-08-12 Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning Zhang, Jie Duan, Yingjing Gu, Xiaoqing Front Psychol Psychology Starting from a pure-image perspective, using machine learning in emotion analysis methods to study artwork is a new cross-cutting approach in the field of literati painting and is an effective supplement to research conducted from the perspectives of aesthetics, philosophy, and history. This study constructed a literati painting emotion dataset. Five classic deep learning models were used to test the dataset and select the most suitable model, which was then improved upon for literati painting emotion analysis based on accuracy and model characteristics. The final training accuracy rate of the improved model was 54.17%. This process visualizes the salient feature areas of the picture in machine vision, analyzes the visualization results, and summarizes the connection law between the picture content of the Chinese literati painting and the emotion expressed by the painter. This study validates the possibility of combining deep learning with Chinese cultural research, provides new ideas for the combination of new technology and traditional Chinese literati painting research, and provides a better understanding of the Chinese cultural spirit and advanced factors. Frontiers Media S.A. 2021-07-28 /pmc/articles/PMC8356227/ /pubmed/34393959 http://dx.doi.org/10.3389/fpsyg.2021.723325 Text en Copyright © 2021 Zhang, Duan and Gu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Zhang, Jie
Duan, Yingjing
Gu, Xiaoqing
Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning
title Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning
title_full Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning
title_fullStr Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning
title_full_unstemmed Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning
title_short Research on Emotion Analysis of Chinese Literati Painting Images Based on Deep Learning
title_sort research on emotion analysis of chinese literati painting images based on deep learning
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356227/
https://www.ncbi.nlm.nih.gov/pubmed/34393959
http://dx.doi.org/10.3389/fpsyg.2021.723325
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