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M. K. Bhandaru and B. A. Draper and V. R. Lesser
ABSTRACT
A common paradigm in object recognition is to extract symbolic and/or numeric features from an image as a preprocessing step for classification. The machine learning and pattern recognition communities have produced many techniques for classifying instances given such features. In contrast, learning to extract a distinguishing set of features that will lead to unambiguous instance classification has received comparatively little attention. We propose a learning paradigm that integrates feature extraction and classifier induction, exploiting their close interrelationship to give improved classification performance. 
ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
Learning Image to Symbol ConversionSite generated on Friday, 06 January 2006