Can Humans and Machines Classify Photographs as Depicting Negation?

Yuri Sato, Koji Mineshima

研究成果: Conference contribution

抄録

How logical concepts such as negation can be visually represented is of central importance in the study of diagrammatic reasoning. To explore various ways in which negation can be visually represented, this study focuses on photographs as instances of purely visual representations. We use real-world photographic image data and study how well humans can classify those images as depicting negation. We also compare the human performance with a state-of-the-art machine (deep) learning model on this classification task. The present paper gives some preliminary results on our data-driven analyses.

本文言語English
ホスト出版物のタイトルDiagrammatic Representation and Inference - 12th International Conference, Diagrams 2021, Proceedings
編集者Amrita Basu, Gem Stapleton, Sven Linker, Catherine Legg, Emmanuel Manalo, Petrucio Viana
出版社Springer Science and Business Media Deutschland GmbH
ページ348-352
ページ数5
ISBN(印刷版)9783030860615
DOI
出版ステータスPublished - 2021
イベント12th International Conference on the Theory and Application of Diagrams, Diagrams 2021 - Virtual, Online
継続期間: 2021 9 282021 9 30

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12909 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference12th International Conference on the Theory and Application of Diagrams, Diagrams 2021
CityVirtual, Online
Period21/9/2821/9/30

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

フィンガープリント

「Can Humans and Machines Classify Photographs as Depicting Negation?」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル