Inner Product Regularized Nonnegative Self Representation for Image Classification and Clustering

Inner Product Regularized Nonnegative Self Representation for Image Classification and Clustering

Feature selection, which aims to select the most informative feature subset, has been playing a critical role in dimension reduction. In this paper, a novel unsupervised feature selection algorithm called the inner product regularized nonnegative self-representation (IRNSR) is designed for image cla...

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Bibliographic Details
Main Authors: Yugen Yi, Wei Zhou, Chao Bi, Guoliang Luo, Yuanlong Cao, Yanjiao Shi
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Unsupervised feature selection
self-representation
inner product regularization
Image classification
image clustering
Online Access:https://ieeexplore.ieee.org/document/7982602/

Internet

https://ieeexplore.ieee.org/document/7982602/

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