Neural Pattern Recognition With Multi-Scale Pyramidal Coding and Selective Attention


Autoria(s): Iizuka, Kunihiko
Data(s)

14/11/2011

14/11/2011

01/07/1993

Resumo

A new neural network architecture for spatial patttern recognition using multi-scale pyramida1 coding is here described. The network has an ARTMAP structure with a new class of ART-module, called Hybrid ART-module, as its front-end processor. Hybrid ART-module, which has processing modules corresponding to each scale channel of multi-scale pyramid, employs channels of finer scales only if it is necesssary to discriminate a pattern from others. This process is effected by serial match tracking. Also the parallel match tracking is used to select the spatial location having most salient feature and limit its attention to that part.

Sharp Corporation

Identificador

http://hdl.handle.net/2144/2023

Publicador

Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems

Relação

BU CAS/CNS Technical Reports;CAS/CNS-TR-1993-046

Direitos

Copyright 1993 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.

Boston University Trustees

Tipo

Technical Report