Ontology driven content mining and semantic queries for satellite image databases

Adrian S. Barb, Chi Ren Shyu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Extracting domain-specific knowledge from image databases is challenging and requires a deep understanding of the domain. For example, in the geospatial domain knowledge discovery computationally expensive due to the huge amount of generated imagery. Existing content-based image retrieval systems utilize models that are trained and optimized to experts' knowledge using expert-in-the-loop approaches. However, such approaches may lead to suboptimal models especially when the number of training images is small. In this paper, we propose incorporating existing domain knowledge resources into knowledge discovery. More specifically, we have developed methods for using ontological relationships between geospatial semantics to oversample under-represented semantics. Our experimental results show that our technique improves the knowledge discovery process, as evidenced by increased precision of semantic queries.

Original languageEnglish (US)
Title of host publication2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages503-506
Number of pages4
Edition1
ISBN (Print)9781424428083
DOIs
StatePublished - 2008
Event2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, United States
Duration: Jul 6 2008Jul 11 2008

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Number1
Volume3

Other

Other2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Country/TerritoryUnited States
CityBoston, MA
Period7/6/087/11/08

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • General Earth and Planetary Sciences

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