Ontological concept extraction based on image understanding and describing of remote sensing domain

Liang Zhong; Hongchao Ma; Pengfei Liu

doi:10.1117/12.747590

15 November 2007 Ontological concept extraction based on image understanding and describing of remote sensing domain

Liang Zhong, Hongchao Ma, Pengfei Liu

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67882M (2007) https://doi.org/10.1117/12.747590
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

When using ontological theory to set up remote sensing image knowledge system, the majority of scholars by now regard ontology as logical theory for defining the object, attribution relation, affair and process of remote sending knowledge system. But understanding and describing the real world makes that logical theory be unable to unify concepts with the same practical meaning from different concept models, so bring grid service system drawbacks in knowledge delivering and sharing. To solve that issue requires further improvement of the defining method and model for concepts in ontology. This paper presents a neural network remote sensing image ontological concept extraction model based on image understanding and describing, utilize the theory of bionic optimization, and adopts the combination of artificial neural network with the rule-based knowledge Recognition System. Realize the knowledge delivering and sharing among different information systems or make the knowledge delivering and sharing between client and system possible and effective.

Citation Download Citation

Liang Zhong, Hongchao Ma, and Pengfei Liu "Ontological concept extraction based on image understanding and describing of remote sensing domain", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67882M (15 November 2007); https://doi.org/10.1117/12.747590

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available