Image analysis – Learning systems – Neural networks
Patent
1992-06-19
1995-08-01
Couso, Yon J.
Image analysis
Learning systems
Neural networks
382159, 395 21, G06K 900
Patent
active
054386292
ABSTRACT:
A classification method and apparatus for classifying an input into one of a plurality of possible outputs. Information representative of the input is compared to a neuron, where the neuron comprises a boundary defined by two or more neuron axes of different length. One of the possible outputs is then selected as corresponding to the input in accordance with that comparison. The invention is also a training method and apparatus for creating a new neuron or adjusting an existing neuron. A feature vector representative of a training input is generated, where the training input corresponds to one of a plurality of possible outputs. If no existing neuron corresponding to the training input encompasses the feature vector, then a new neuron is created, where the new neuron comprises a boundary defined by two or more neuron axes of different length. If the neuron encompasses the feature vector and if the neuron does not correspond to the training input, then the neuron is adjusted spatially, where the adjusted neuron comprises a boundary defined by two or more adjusted neuron axes of different length.
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Lee Chih-Ping
Moed Michael C.
Couso Yon J.
Mendelsohn Steve
Murray William H.
United Parcel Service of America Inc.
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