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

  • 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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Metadaten
Author:Uwe R. Zimmer, Jörg Bruske, Ewald von Puttkamer
URN (permanent link):urn:nbn:de:hbz:386-kluedo-2954
Document Type:Preprint
Language of publication:English
Year of Completion:1993
Year of Publication:1993
Publishing Institute:Technische Universität Kaiserslautern
Source:ANZIIS 93, Perth Western Australia
Faculties / Organisational entities:Fachbereich Informatik
DDC-Cassification:004 Datenverarbeitung; Informatik

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