
Proceedings Paper
Adaptive kernels for morphological heteroassociative neural networksFormat | Member Price | Non-Member Price |
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Paper Abstract
Morphological Neural Networks (MNN) have been proposed as an alternative neural computation paradigm. In this paper we explore the potential of Heteroassociative MNN (HMNN) for a vision based practical task, that of self-localization in a vision-based navigation framework for mobile robots. HMNN have a big potential for real time application because its recall process is very fast. We present some experimental results that illustrate the proposed approach.
Paper Details
Date Published: 4 April 2001
PDF: 8 pages
Proc. SPIE 4305, Applications of Artificial Neural Networks in Image Processing VI, (4 April 2001); doi: 10.1117/12.420934
Published in SPIE Proceedings Vol. 4305:
Applications of Artificial Neural Networks in Image Processing VI
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)
PDF: 8 pages
Proc. SPIE 4305, Applications of Artificial Neural Networks in Image Processing VI, (4 April 2001); doi: 10.1117/12.420934
Show Author Affiliations
Manuel Grana Romay, Univ. Pais Vasco (Spain)
Bogdan Raducanu, Univ. Pais Vasco (Spain)
Published in SPIE Proceedings Vol. 4305:
Applications of Artificial Neural Networks in Image Processing VI
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)
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