KNOWLEDGE BASED 3D-MODELLING BY SELFORGANISED LEARNING ALGORITHMS - Image understanding based on automated knowledge refinement

Eckhard Büscher

2004

Abstract

This paper discusses the design and implementation of a knowledge based Modelling system KMS, which combines semantic and rule based approaches in the modelling process. The design and implementation of the semantic concepts are controlled dynamically to achieve an optimal degree of reality and to employ efficient interactivity and accessibility for the user. The model-based controlling module is developed to achieve efficiency and consistence in the basic analysis process, and to avoid the static structure that frequently occurs in data driven systems. By using a hypothesis and verification scheme in order to ensure interactivity and accessibility without sacrificing efficiency the KMS evokes the important task of merging the use of heuristic knowledge in form of a knowledge base with domain specific requirements. By detecting contradicting and inconsistent rules and by performing tests in the knowledge base and finally by creating new hypothesis to solve the problems, the controlling process also provides the decision module with a concept for automated knowledge refinement. This paper focuses on the implementation and Multimedia adaptation of the learning processes in correlation with the linked databases.

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Paper Citation


in Harvard Style

Büscher E. (2004). KNOWLEDGE BASED 3D-MODELLING BY SELFORGANISED LEARNING ALGORITHMS - Image understanding based on automated knowledge refinement . In Proceedings of the First International Conference on E-Business and Telecommunication Networks - Volume 3: ICETE, ISBN 972-8865-15-5, pages 356-362. DOI: 10.5220/0001399203560362


in Bibtex Style

@conference{icete04,
author={Eckhard Büscher},
title={KNOWLEDGE BASED 3D-MODELLING BY SELFORGANISED LEARNING ALGORITHMS - Image understanding based on automated knowledge refinement },
booktitle={Proceedings of the First International Conference on E-Business and Telecommunication Networks - Volume 3: ICETE,},
year={2004},
pages={356-362},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001399203560362},
isbn={972-8865-15-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on E-Business and Telecommunication Networks - Volume 3: ICETE,
TI - KNOWLEDGE BASED 3D-MODELLING BY SELFORGANISED LEARNING ALGORITHMS - Image understanding based on automated knowledge refinement
SN - 972-8865-15-5
AU - Büscher E.
PY - 2004
SP - 356
EP - 362
DO - 10.5220/0001399203560362