Abstract | ||
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TAM (Topographic Attentive Mapping) network is a biologically-motivated neural network with Gabor function type receptive fields. However, the structure of receptive fields is a mono-layer, and there is a lack of performance for rotating images. In this paper, we formulate a new TAM network with multilayer structurr of extensive receptive fields. We also show the usefulness of TAM network using some examples of character recognition. |
Year | DOI | Venue |
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2005 | 10.1109/CIMCA.2005.1631423 | CIMCA/IAWTIC |
Keywords | Field | DocType |
new tam network,extensive receptive field,multilayer structurr,receptive field,orientation selectivity,topographic attentive mapping,character recognition,tam network,gabor function type,biologically-motivated neural network,neural nets,neural network | Receptive field,Computer vision,Character recognition,Pattern recognition,Topographic map,Computer science,Image rotation,Function type,Artificial intelligence,Artificial neural network,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2504-0-01 | 0 | 0.34 |
References | Authors | |
6 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Isao Hayashi | 1 | 276 | 85.75 |
James R. Williamson | 2 | 389 | 31.64 |