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Stratified regularity measures with Jensen-Shannon divergence
2008
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
This paper proposes a stratified regularity measure: a novel entropic measure to describe data regularity as a function of data domain stratification. Jensen-Shannon divergence is used to compute a set-similarity of intensity distributions derived from stratified data. We prove that derived regularity measures form a continuum as a function of the stratification's granularity and also upper-bounded by the Shannon entropy. This enables to interpret it as a generalized Shannon entropy with an
doi:10.1109/cvprw.2008.4563020
dblp:conf/cvpr/OkadaPB08
fatcat:ychcywqkz5g3hk7n3quvq6msyi