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ICCV
2005
IEEE

A Generative/Discriminative Learning Algorithm for Image Classification

14 years 4 months ago
A Generative/Discriminative Learning Algorithm for Image Classification
We have developed a two-phase generative / discriminative learning procedure for the recognition of classes of objects and concepts in outdoor scenes. Our method uses both multiple types of object features and context within the image. The generative phase normalizes the description length of images, which can have an arbitrary number of extracted features of each type. In the discriminative phase, a classifier learns which images, as represented by this fixed-length description, contain the target object. We have tested the approach by comparing it to several other approaches in the literature and by experimenting with several different data sets and combinations of features. Our results, using color, texture, and structure features, show a significant improvement over previously published results in image retrieval. Using salient region features, we are competitive with recent results in object recognition.
Yi Li, Linda G. Shapiro, Jeff A. Bilmes
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 2005
Where ICCV
Authors Yi Li, Linda G. Shapiro, Jeff A. Bilmes
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