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Titlebook: Applied Pattern Recognition; Horst Bunke,Abraham Kandel,Mark Last Book 2008 Springer-Verlag Berlin Heidelberg 2008 Markov.Statistica.Wavel

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https://doi.org/10.1007/978-3-642-48597-8 set function in 4D space that exploits the coherence within continuous regions not only between spatial slices, but between consecutive time samples as well. Shape priors are incorporated into the segmentation to limit the result to a known shape. Variations in shape are computed using principal co
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Entwürfe zu Festsetzungen über Lebensmittelegarded in favor of employing model graphs tailored to specific object categories like faces in frontal pose. Invariant recognition or categorization of arbitrary objects, however, demands dynamic graphs..In this work we propose a form of graph dynamics which proceeds in three steps. In the first st
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Face Recognition and Pose Estimation with Parametric Linear Subspaces unfamiliar cases by avoiding overfitting. We apply the model to realize robust pose estimation using the view-to-pose mapping and pose-invariant face recognition using the proposed model to represent a known face. Quantitative experiments are conducted using a database of Cyberware-scanned 3D face
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4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors set function in 4D space that exploits the coherence within continuous regions not only between spatial slices, but between consecutive time samples as well. Shape priors are incorporated into the segmentation to limit the result to a known shape. Variations in shape are computed using principal co
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