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
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
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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