The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Neural network model for selective attention in visual pattern recognition and associative recall
Abstract
A neural network model of selective attention is discussed. When two patterns or more are presented simultaneously, the model successively pays selective attention to each one, segmenting it from the rest and recognizing it separately. In the presence of noise or defects, the model can recall the complete pattern in which the noise has been eliminated and the defects corrected. These operations can be successfully performed regardless of deformation of the input patterns. This is an improved version of the earlier model proposed by the author: the ability of segmentation is improved by lateral inhibition.
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Citations
Cites
Fukushima, K. (1980) · Biological Cybernetics · doi:10.1007/bf00344251 · Cited by 5,759
Self-citationCompetitive learning: From interactive activation to adaptive resonance
Grossberg, S. (1987) · Cognitive Science · doi:10.1111/j.1551-6708.1987.tb00862.x · Cited by 1,471
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Metadata
- Authors
- Fukushima, K.
- Venue
- Applied Optics
- Publisher
- Optica Publishing Group
- Published
- 1987-12-01
- Volume
- 26
- Issue
- 23
- Pages
- 4985
- ISSN
- 0003-6935 (ISSN-L)
- 1539-4522
- OpenAlex
- W2065981956
- Cited by
- 176
- References
- 2
- FWCI
- 5.24
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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