NDLI: Classification of high-dimensional data using the Sparse Matrix Transform

Content Provider	IEEE Xplore Digital Library
Author	Bachega, L.R. Bouman, C.A.
Copyright Year	2010
Description	Author affiliation: Purdue University, School of Electrical and Computer Engineering, West Lafayette, IN, 47907-2035, USA (Bachega, L.R.; Bouman, C.A.)
Abstract	In this paper, we develop a classification method for high-dimensional data based on the Sparse Matrix Transform (SMT). The recently proposed SMT has been shown to produce more accurate estimates of covariance matrices when the number of training samples n is much less than the number of dimensions p of the data. Here we introduce a classifier that uses the SMT to model the covariance structure of the data. Experiments in face recognition using the FERET face database show that our method is superior to a conceptually very similar and low-dimensional method in at least two key aspects: First, the SMT classifier is more robust to the size of the training set, remaining accurate even when only a few training samples are available; Second, the total computation required to apply the SMT classifier to high-dimensional data is very low, making this method attractive for use in low-power and mobile devices, or in application settings requiring fast computation
Starting Page	265
Ending Page	268
File Size	178642
Page Count	4
File Format	PDF
ISBN	9781424479924
ISSN	15224880
e-ISBN	9781424479948
e-ISBN	9781424479931
DOI	10.1109/ICIP.2010.5652690
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-26
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Face Accuracy Transforms Sparse matrices Covariance matrix Face recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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