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Abstract

A produce recognition method which uses hierarchical Bayesian learning and kernel combination, and which offers classification-oriented synergistic data integration from diverse sources. An example method includes providing a classifier having a plurality of inputs, each input being adapted to receive produce data of a different modality; mapping the produce data to the respective input of the classifier by a computer; for each input, independently operating on the data relating to that input to create a feature set by the computer; comparing each feature in the feature set to respective pre-trained data for that feature to produce a similarity description set; combining all similarity description sets using a dedicated weighting function to produce a composite similarity description by the computer; and deriving a plurality of class values from the composite similarity description to create a recognition result for the produce item by the computer.

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First Claim