Data di Pubblicazione:
2002
Abstract:
In recent years, there have been several proposals for the realization of models inspired to biological solutions for pattern recognition.
In this work we propose a new approach, based on a hierarchical modular
structure, to realize a system capable to learn by examples and recognize
objects in digital images. The adopted techniques are based on multiresolution
image analysis and neural networks. Performance on two different data sets and
experimental timings on a single instruction multiple data (SIMD) machine are
also reported.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Object Recognition; Pyramidal Neural Networks; Attentive Vision; High Performance Computing; SIMD Computation
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