ScholarLens Back to search
2023•˜The œKyoto Conference on Arts, Media & Culture official conference proceedingsOpen access

Using Machine Learning to Classify Art Style in Naturalism and Realism

Maftuhah Rahimah Rum, Ardha Ardea Prisilla, Yori Pusparani, Wen-Hung Chao, Chi-Wen Lung

Open full text 0 citations

Abstract

This paper is part of the KAMC2023 Conference Proceedings (View) Full Paper View / Download the full paper in a new tab/window

Open-access reader

About this research paper

What this paper is about

This paper is part of the KAMC2023 Conference Proceedings (View) Full Paper View / Download the full paper in a new tab/window

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

This paper is part of the KAMC2023 Conference Proceedings (View) Full Paper View / Download the full paper in a new tab/window

Key concepts: Naturalism, Realism, Style (visual arts), Aesthetics, Learning styles, Critical realism (philosophy of perception), Epistemology, Psychology

Related papers

Related paper 1Related paper 2
Back to paper searchBrowse research topicsOriginal source
Using Machine Learning to Classify Art Style in Naturalism and Realism — Research Paper | ScholarLens