Method and apparatus for hierarchical input classification using a neural network
First Claim
1. A method for classifying an input into one of a plurality of possible outputs, comprising the steps of:
- (a) applying a top-level classifier to the input to generate an approximate identification for the input as one of the possible outputs;
(b) using the approximate identification to select a subset of available cluster classifiers;
(c) applying said selected cluster classifiers to the input to generate two or more identifications for the input as one or more of the possible outputs; and
(d) classifying the input as one of the possible outputs in accordance with said two or more identifications.
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Abstract
An input is classified into one of a plurality of possible outputs. A top-level classifier generates an approximate identification for the input as one of the possible outputs and selects two or more neural networks corresponding to the approximate identification. The selected neural networks generate two or more identifications for the input as one or more of the possible outputs. A postprocessor classifies the input as one of the possible outputs in accordance with the two or more identifications of the selected neural networks. According to an alternative embodiment, a top-level classifier selects a subset of neurons of a neural network and the subset of neurons identifies the input as one of the possible outputs.
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Citations
18 Claims
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1. A method for classifying an input into one of a plurality of possible outputs, comprising the steps of:
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(a) applying a top-level classifier to the input to generate an approximate identification for the input as one of the possible outputs; (b) using the approximate identification to select a subset of available cluster classifiers; (c) applying said selected cluster classifiers to the input to generate two or more identifications for the input as one or more of the possible outputs; and (d) classifying the input as one of the possible outputs in accordance with said two or more identifications. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A system for classifying an input into one of a plurality of possible outputs, comprising:
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(a) means for applying a top-level classifier to the input to generate an approximate identification for the input as one of the possible outputs; (b) means for using the approximate identification to select a subset of available cluster classifiers; (c) means for applying said selected cluster classifiers to the input to generate two or more identifications for the input as one or more of the possible outputs; and (d) means for classifying the input as one of the possible outputs in accordance with said two or more identifications. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A system for classifying an input into one of a plurality of possible outputs, comprising:
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(a) a top-level classifier; (b) a plurality of cluster classifiers; and (c) a postprocessor, wherein; the top-level classifier generates an approximate identification for the input as one of the possible outputs and uses the approximate identification to select a subset of the cluster classifiers; the selected cluster classifiers generate two or more identifications for the input as one or more of the possible outputs; and the postprocessor classifies the input as one of the possible outputs in accordance with the two or more identifications of the cluster classifiers. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification