Title :
Neural recognition in a pyramidal structure
Author :
Cantoni, Virginio ; Petrosino, Alfredo
Author_Institution :
Dipt. di Inf. e Sistemistica, Pavia Univ., Italy
fDate :
3/1/2002 12:00:00 AM
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
Keywords :
image recognition; neural net architecture; parallel architectures; pattern recognition; multiresolution image analysis; neural networks; parallel machine; pattern recognition; single instruction multiple data machine; structured neural network; Biological system modeling; Digital images; Feature extraction; Hopfield neural networks; Image analysis; Image recognition; Image resolution; Neural networks; Pattern recognition; Proposals;
Journal_Title :
Neural Networks, IEEE Transactions on
