Invention Grant
- Patent Title: Metric learning for nearest class mean classifiers
- Patent Title (中): 最近类平均分类器的度量学习
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Application No.: US13561655Application Date: 2012-07-30
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Publication No.: US09031331B2Publication Date: 2015-05-12
- Inventor: Thomas Mensink , Jakob Verbeek , Gabriela Csurka , Florent Perronnin
- Applicant: Thomas Mensink , Jakob Verbeek , Gabriela Csurka , Florent Perronnin
- Applicant Address: US CT Norwalk
- Assignee: Xerox Corporation
- Current Assignee: Xerox Corporation
- Current Assignee Address: US CT Norwalk
- Agency: Fay Sharpe LLP
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/00

Abstract:
A classification system and method enable improvements to classification with nearest class mean classifiers by computing a comparison measure between a multidimensional representation of a new sample and a respective multidimensional class representation embedded into a space of lower dimensionality than that of the multidimensional representations. The embedding is performed with a projection that has been learned on labeled samples to optimize classification with respect to multidimensional class representations for classes which may be the same or different from those used subsequently for classification. Each multidimensional class representation is computed as a function of a set of multidimensional representations of labeled samples, each labeled with the respective class. A class is assigned to the new sample based on the computed comparison measures.
Public/Granted literature
- US20140029839A1 METRIC LEARNING FOR NEAREST CLASS MEAN CLASSIFIERS Public/Granted day:2014-01-30
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