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SUMMARY:MBO method for image processing and classification using a graphic
 al framework
DTSTART:20150703T140000
DTSTAMP:20260407T102424Z
UID:ae40cc1f37fa344c207bfeb0543e7ce5dbd0e9c46b3873cc3cacdf81
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Ekaterina Merkurjev\, UCLA\nWe present a graph-based algor
 ithm for image processing and classification of high-dimensional data. The
  semi-supervised method uses a graph adaptation of the classical numerical
  Merriman-Bence-Osher (MBO) scheme\, and can be extended to the multiclass
  case via the Gibbs simplex. We show examples of the application of the al
 gorithm in the areas of image inpainting\, image segmentation and object d
 etection using hyperspectral video sequences.\nBio: Solid background in ap
 plied and computational mathematics\, differential equations\, numerical a
 nalysis\, optimization\, scientific computing.\nVariational and PDE-based 
 methods for machine learning\, data analysis\, and image processing using 
 a graphical framework. Applications include classification of high-dimensi
 onal data\, image segmentation and image inpainting.
LOCATION:INF119
STATUS:CONFIRMED
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