Style-Consistency in Isogenous Patterns
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Style-constrained quadratic field classifiers
Style-constrained quadratic field classifiers
Analytical Results on Style-Constrained Bayesian Classification of Pattern Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive, mobile, distributed pattern recognition
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
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In style-constrained classification often there are onlya few samples of each style and class, and the correspondencesbetween styles in the training set and the test setare unknown. To avoid gross misestimates of the classifierparameters it is therefore important to model the patterndistributions accurately. We offer empirical evidence for intuitivelyappealing assumptions, in feature spaces appropriatefor symbolic patterns, for (1) tetrahedral configurationsof class means that suggests linear style-adaptive classification,(2) improved estimates of classification boundariesby taking into account the asymmetric configuration of thepatterns with respect to the directions toward other classes,and (3) pattern-correlated style variability.