Abstract: A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.

Abstract: Face detection techniques are provided that use a multiple-stage face detection algorithm. An exemplary three-stage algorithm includes a first stage that applies linear-filtering to enhance detection performance by removing many non-face-like portions within an image, a second stage that uses a boosting chain that is adopted to combine boosting classifiers within a hierarchy “chain” structure, and a third stage that performs post-filtering using image pre-processing, SVM-filtering and color-filtering to refine the final face detection prediction. In certain further implementations, the face detection techniques include a two-level hierarchy in-plane pose estimator to provide a rapid multi-view face detector that further improves the accuracy and robustness of face detection.

Abstract: Disclosed are dentifrice compositions comprising in a single phase: (a) from about 0.1% to about 30% of one or more linear polyphosphates having an average chain length of about 4 or more; (b) an ionic active ingredient selected from the group consisting of a fluoride ion source, a stannous ion source, a zinc ion source, a copper ion source and mixtures thereof, wherein the ionic active ingredient is present as a solid dispersion in the composition and delivers and effective amount of ionic active when solubilized; (c) a binder system comprised of (i) from about 0.05% to about 3% of a thickening agent selected from the group consisting of polysaccharides, carbomers, poloxamers, modified celluloses, and mixtures thereof; and (ii) from about 0.1% to about 70% of at least one humectant; wherein the dentifrice composition has a total water content of less than about 10%. Further disclosed are methods for stabilizing dentifrice compositions by providing such a binder system.

Abstract: Disclosed are dentifrice compositions comprising in a single phase: (a) from about 0.1% to about 30% of one or more linear polyphosphates having an average chain length of about 4 or more; (b) an ionic active ingredient selected from the group consisting of a fluoride ion source, a stannous ion source, a zinc ion source, a copper ion source and mixtures thereof, wherein the ionic active ingredient is present as a solid dispersion in the composition and delivers and effective amount of ionic active when solubilized; (c) a binder system comprised of (i) from about 0.05% to about 3% of a thickening agent selected from the group consisting of polysaccharides, carbomers, poloxamers, modified celluloses, and mixtures thereof; and (ii) from about 0.1% to about 70% of at least one humectant; wherein the dentifrice composition has a total water content of less than about 10%. Further disclosed are methods for stabilizing dentifrice compositions by providing such a binder system.

Abstract: A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.