Learning and Preset Knowledge for Surface Fusion
A Neural Fuzzy Decision System

ANZIIS '93, Perth, Western Australia, December 1-3, 1993

Joerg Bruske, Ewald von Puttkamer & Uwe R. Zimmer - contact authors

The problem to be discussed in this paper may be characterized in short by the question: "Are these two surface fragments belonging together (i.e. belonging to the same surface)?". The presented techniques try to benefit from some predefined knowledge as well as from the possibility to refine and adapt this knowledge according to a (changing) real environment, resulting in a combination of fuzzy-decision systems and neural networks. The results are encouraging (fast convergence speed, high accuracy), and the model might be used for a wide range of applications. The general frame surrounding the work in this paper is the SPIN-project, where emphasis is on sub-symbolic abstractions, based on a 3-d scanned environment.

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