Name
Abstract | ||
|---|---|---|
TAM (Topographic Attentive Mapping) network is a biologically- motivated neural network with receptive fields of Gabor function. However, the receptive field's layer is monotype, and there is a lack of performance for rotating visual images. In this paper, we formulate four TAM networks with multilayer structure of extensive receptive fields. We discuss their performance and show the usefulness of TAM network using some examples of character recognition. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICSMC.2006.384936 | 2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS |
Keywords | Field | DocType |
optical character recognition,neural nets,neural network,receptive field | Receptive field,Character recognition,Topographic map,Computer science,Optical character recognition,Artificial intelligence,Artificial neural network,Machine learning | Conference |
ISSN | Citations | PageRank |
1062-922X | 2 | 0.38 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Isao Hayashi | 1 | 276 | 85.75 |
| Toshiyuki Maeda | 2 | 213 | 25.86 |