Category learning through multimodality sensing

Category learning through multimodality sensing (1998)

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by Virginia R. De Sa , Dana H. Ballard

Venue:	Neural Computation
Citations:	38 - 4 self

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@ARTICLE{Sa98categorylearning,
    author = {Virginia R. De Sa and Dana H. Ballard},
    title = {Category learning through multimodality sensing},
    journal = {Neural Computation},
    year = {1998},
    volume = {10},
    pages = {1097--1117}
}

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Abstract

Humans and other animals learn to form complex categories without receiving a target output, or teaching signal, with each input pattern. In contrast, most computer algorithms that emulate such performance assume the brain is provided with the correct output at the neuronal level or require grossly unphysiological methods of information propagation. While natural environments do not contain explicit labeling signals, they do contain important information in the form of temporal correlations between sensations to di erent sensory modalities and humans are a ected by this correlational

Citations

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