Identifying anomalous object types during classification

Techniques are disclosed for identifying anomaly object types during classification of foreground objects extracted from image data. A self-organizing map and adaptive resonance theory (SOM-ART) network is used to discover object type clusters and classify objects depicted in the image data based on...

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Bibliographische Detailangaben

Hauptverfasser:	COBB WESLEY KENNETH, XU GANG, SEOW MING-JUNG, FRIEDLANDER DAVID, GOTTUMUKKAL RAJKIRAN KUMAR
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTING COUNTING DETECTING MASSES OR OBJECTS GEOPHYSICS GRAVITATIONAL MEASUREMENTS HANDLING RECORD CARRIERS MEASURING PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS TESTING
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