Learning system with prototype replacement
First Claim
1. An adaptive classifier apparatus comprising:
- means for scanning a test object and outputting a parameter signal representing a scanned physical parameter of the test object;
means for receiving said parameter signal and for generating a test feature data based on said parameter signal;
means for retrievably storing a first plurality of a prototype feature data and a second plurality of a prototype feature data;
classifying means for comparing said test feature data to each of said first plurality and to each of said second plurality of prototype feature data and for generating a classifier data indicating which of said first plurality and said second plurality has a prototype feature data comparing closest to said test feature data;
means for generating an event signal associated with said generating a classifier data;
means for generating a usefulness data corresponding to each of said first plurality and said second plurality of prototype feature data, said usefulness data representing a frequency and recency relative to said event signal that its associated prototype feature datum is the prototype feature datum comparing closest with the test feature;
means for modifying said stored first plurality of prototype feature data and said stored second plurality of prototype feature data based on said usefulness data.
1 Assignment
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Accused Products
Abstract
One or more sets of prototype descriptions for a number of classes of objects stored on a computer database are maintained. These prototypes are used as a basis for identifying the class of a presented object. A trainer determines when a new prototype is required to be added to the database based on current match results. This allows the system to be trained to recognize items in classes that deviate significantly from the items that were initially used to determine the classification rules. A determination is made about which prototypes can be deleted on the basis of their match histories. This allows the system to automatically optimize itself to work with a bounded collection of prototypes. In addition, it allows the system to track variations in class characteristics over time and adjust the corresponding set of prototypes appropriately.
94 Citations
15 Claims
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1. An adaptive classifier apparatus comprising:
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means for scanning a test object and outputting a parameter signal representing a scanned physical parameter of the test object; means for receiving said parameter signal and for generating a test feature data based on said parameter signal; means for retrievably storing a first plurality of a prototype feature data and a second plurality of a prototype feature data; classifying means for comparing said test feature data to each of said first plurality and to each of said second plurality of prototype feature data and for generating a classifier data indicating which of said first plurality and said second plurality has a prototype feature data comparing closest to said test feature data; means for generating an event signal associated with said generating a classifier data; means for generating a usefulness data corresponding to each of said first plurality and said second plurality of prototype feature data, said usefulness data representing a frequency and recency relative to said event signal that its associated prototype feature datum is the prototype feature datum comparing closest with the test feature; means for modifying said stored first plurality of prototype feature data and said stored second plurality of prototype feature data based on said usefulness data. - View Dependent Claims (2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15)
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7. An adaptive classifier apparatus according to claim wherein said visual characteristic of the test object is a texture characteristic and wherein said prototype visual characteristics are texture characteristics.
Specification