Intrinsic Metric Learning With Subspace Representation

Intrinsic Metric Learning With Subspace Representation

The accuracy of classification and retrieval significantly depends on the metric used to compute the similarity between samples. For preserving the geometric structure, the symmetric positive definite (SPD) manifold is introduced into the metric learning problem. However, the SPD constraint is too s...

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Bibliographic Details
Main Authors: Lipeng Cai, Shihui Ying, Yaxin Peng, Changzhou He, Shaoyi Du
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Metric learning
subspace representation
low-rank optimization
structure preserving
image classification
Online Access:https://ieeexplore.ieee.org/document/8719971/

Internet

https://ieeexplore.ieee.org/document/8719971/

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