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

抄録

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.'.

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

出版物シリーズ

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

ASJC Scopus subject areas

  • Artificial Intelligence

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