Generalized Robust PCA: A New Distance Metric Method for Underwater Target Recognition
Inspired by the importance of distance metrics and the structure-preserving ability of features, a novel recognition method for underwater targets, called generalized robust principal component analysis (GRPCA), is proposed in this paper. Several advantages of GRPCA are summarized as follows. First,...
Main Authors: | Jian Xu, Pengfei Bi, Xue Du, Juan Li, Dong Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8691451/ |
Similar Items
-
Application of Locally Invariant Robust PCA for Underwater Image Recognition
by: Pengfei Bi, et al.
Published: (2021-01-01) -
Underwater Target Noise Recognition and Classification Technology based on Multi-Classes Feature Fusion
Published: (2020-04-01) -
An Observability Metric for Underwater Vehicle Localization Using Range Measurements
by: Filippo Arrichiello, et al.
Published: (2013-11-01) -
Robust principal component analysis via projection pursuit
by: Patak, Zdenek
Published: (2010) -
Robust Flow Field Signal Estimation Method for Flow Sensing by Underwater Robotics
by: Xinghua Lin, et al.
Published: (2021-08-01)