2024-03-28T18:23:17Z
https://repository.dl.itc.u-tokyo.ac.jp/oai
oai:repository.dl.itc.u-tokyo.ac.jp:00054617
2022-12-19T05:09:41Z
67:68:4399:8488
9:504:4401:8489
Reorganization Impressionism : A Proposal for a New Methodology Using Machine Learning
印象主義絵画再編 : 機械学習による新解釈手法の提案
原, 翔子
162533
決定木
クラスタリング
19 世紀フランス社会
キャリア
印象主義絵画
ネットワーク分析
Machine Learning
Clustering
19th Century French Society
Career
Impressionism
Network Analysis
The purpose of this study is to organize and consider artwork from a quantitative point of view. Therefore, the decision tree, which is a classification method of machine learning, is applied on 120 impressionist paintings from the Chicago Institute of Fine Arts. Through this classification, a different viewpoint from the past in interpreting the picture work has been obtained. Moreover, this new method may provide comprehensive interpretation of paintings with additional information such as the situation at the time of production, metadata, etc., instead of simply focusing on each painting.
査読研究論文
Refereed Papers
departmental bulletin paper
東京大学大学院情報学環
2020-10-30
application/pdf
情報学研究 : 学環 : 東京大学大学院情報学環紀要
99
17
31
AA12032633
1880697X
21878056
https://repository.dl.itc.u-tokyo.ac.jp/record/54617/files/99_3.pdf
jpn