Multi-Dimensional Semantic Computing with Spatial-Temporal and Semantic Axes for Multi-spectrum Images in Environment Analysis

Yasushi Kiyoki, Xing Chen, Shiori Sasaki, Chawan Koopipat

研究成果: Conference contribution

抜粋

Semantic computing is an important and promising approach to semantic analysis for various environmental phenomena and changes in real world. This paper presents a new semantic computing method with multi-spectrum images for analyzing and interpreting environmental phenomena and changes occurring in the physical world. We have already presented a concept of 'Semantic Computing System' for realizing global environmental analysis. This paper presents a new semantic computing method to realize semantic associative search for the multiple-colours-spectrum images in the multi-dimensional semantic space, that is 'multi-spectrum semantic-image space' with semantic projection functions. This space is created for dynamically computing semantic equivalence, similarity and difference between multi-spectrum images and environmental situations. We apply this system to global environmental analysis as a new platform of environmental computing. We have already presented the 5D World Map System, as an international research environment with spatio-temporal and semantic analysers. We also present several new approaches to global environmental-analysis for multi-spectrum images in 'multi-spectrum semantic-image space.'.

元の言語English
ホスト出版物のタイトルInformation Modelling and Knowledge Bases XXVII
出版者IOS Press
ページ14-30
ページ数17
280
ISBN(印刷物)9781614996101
DOI
出版物ステータスPublished - 2016

出版物シリーズ

名前Frontiers in Artificial Intelligence and Applications
280
ISSN(印刷物)09226389

    フィンガープリント

ASJC Scopus subject areas

  • Artificial Intelligence

これを引用

Kiyoki, Y., Chen, X., Sasaki, S., & Koopipat, C. (2016). Multi-Dimensional Semantic Computing with Spatial-Temporal and Semantic Axes for Multi-spectrum Images in Environment Analysis. : Information Modelling and Knowledge Bases XXVII (巻 280, pp. 14-30). (Frontiers in Artificial Intelligence and Applications; 巻数 280). IOS Press. https://doi.org/10.3233/978-1-61499-611-8-14