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Manifold Blurring Mean Shift Algorithms for Manifold Denoising
Miguel Á. Carreira-Perpiñán
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Oznake: computer science;machine learning;manifold learning;computer vision
We propose a new family of algorithms for denoising data assumed to lie on a low-dimensional manifold. The algorithms are based on the blurring mean-shift update, which moves each data point towards its neighbors, but constrain the motion to be orthogonal to the manifold. The resulting algorithms ar ...
Leto: 2010 Vir: videolectures.net
Poster Spotlights
Qingxiong Yang , Sing Bing Kang , Stefan Holzer , Jonathan Brandt , Nils Hasler , Anat Levin , Jingchen Liu , Xiuzhuang Zhou , Gianfranco Doretto , Pawan Kumar Mudigonda , Julian McAuley , Bernhard Zeisl , Kaushik Mitra , Miguel Á. Carreira-Perpiñán , Nitesh Shroff , Leo Zhu , Teng Zhang , Andrew Kae , Armand Joulin
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Oznake: computer science;computer vision;machine learning
Leto: 2010 Vir: videolectures.net
Št. zadetkov: 2
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