Title :
Neural pattern recognition with multi-scale pyramidal coding and selective attention
Author :
Iizuka, Kunihiko
Author_Institution :
Center for Adaptive Syst., Boston Univ., MA, USA
Abstract :
A new neural network architecture for spatial pattern recognition using multi-scale pyramidal coding is described. The network has an ARTMAP structure with a new class of ART-module, called hybrid ART-module, as its front-end processor. The 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 necessary 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.
Keywords :
ART neural nets; encoding; learning (artificial intelligence); neural net architecture; parallel processing; pattern recognition; ARTMAP structure; hybrid ART-module; multi-scale pyramidal coding; neural network architecture; parallel match tracking; selective attention; serial match tracking; spatial pattern recognition; Adaptive systems; Humans; Image resolution; Neural networks; Pattern matching; Pattern recognition; Resonance; Signal processing; Streaming media; Subspace constraints;
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
DOI :
10.1109/IJCNN.1993.716801