Invention Grant
US09471847B2 Efficient distance metric learning for fine-grained visual categorization
有权
高效的距离度量学习，用于细粒度视觉分类
- Patent Title: Efficient distance metric learning for fine-grained visual categorization
- Patent Title (中): 高效的距离度量学习，用于细粒度视觉分类
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Application No.: US14524441Application Date: 2014-10-27
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Publication No.: US09471847B2Publication Date: 2016-10-18
- Inventor: Shenghuo Zhu , Yuanqing Lin , Qi Qian
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: JP
- Assignee: NEC Corporation
- Current Assignee: NEC Corporation
- Current Assignee Address: JP
- Agent Joseph Kolodka
- Main IPC: G06K9/62
- IPC: G06K9/62
Abstract:
Methods and systems for distance metric learning include generating two random projection matrices of a dataset from a d-dimensional space into an m-dimensional sub-space, where m is smaller than d. An optimization problem is solved in the m-dimensional subspace to learn a distance metric based on the random projection matrices. The distance metric is recovered in the d-dimensional space.
Public/Granted literature
- US20150117764A1 EFFICIENT DISTANCE METRIC LEARNING FOR FINE-GRAINED VISUAL CATEGORIZATION Public/Granted day:2015-04-30
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