NDLI: Sparse Non-negative Pattern Learning for image representation

Content Provider	IEEE Xplore Digital Library
Author	Dian Gong Xuemei Zhao Qiong Yang
Copyright Year	2008
Description	Author affiliation: ESAT-PSI/VISICS, Katholieke Univ. Leuven, Leuven (Qiong Yang) \|\| Dept. of Electron. Eng., Tsinghua Univ., Beijing (Xuemei Zhao) \|\| Dept. of Electr. Eng., Univ. of California, Riverside, CA (Dian Gong)
Abstract	In this paper, we propose sparse non-negative pattern learning (SNPL) based on self-taught learning framework. In the algorithm, visual patterns are first learned from unlabeled data by non-negative matrix approximation with sparseness constraints, and then features are extracted by the second part of the algorithm, a conjugate family based non-negative sparse feature extraction method. By combining sparse and non-negative constraints of patterns together, SNPL model gives a better representation for images than state-of-art methods. Beyond that, we give an analytical solution for feature extraction although it is approximate, and thereby we extract the features for self-taught learning framework in a faster and more stable way. We apply the new model to various areas, including pattern coding, feature extraction, and recognition. Experimental results show the advantages of SNPL model.
Starting Page	981
Ending Page	984
File Size	250081
Page Count	4
File Format	PDF
ISBN	9781424417650
ISSN	15224880
DOI	10.1109/ICIP.2008.4711921
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image representation Feature extraction Data mining Approximation algorithms Sparse matrices Machine learning Principal component analysis Independent component analysis Testing Pattern recognition Feature Extraction Self Learning Non-negative Matrix Approximation Pattern Learning Sparse Representation
Content Type	Text
Resource Type	Article

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