NDLI: New Method Based on Support Vector Machine in Classification for Hyperspectral Data

Content Provider	IEEE Xplore Digital Library
Author	Xiangtao Wang Yan Feng
Copyright Year	2008
Description	Author affiliation: Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi'an (Xiangtao Wang; Yan Feng)
Abstract	Cross-validation is a normal method for parameter selection of support vector machine (SVM) which is a novel machine learning method for hyperspectral data classification. Because of the high dimensionality of hyperspectral data, the process of cross-validation will cost more time. For reducing the time of cross-validation and improving classification accuracy, a new combination method of improving sequential minimal optimization (SMO), independent component analysis (ICA) and mixture kernels is proposed. It can be described as follows: first use the improving SMO method to optimize the model of SVM, and then use ICA method to do dimensionality reduction before cross-validation, at last use mixture kernels to do classification of unknown samples. By the experiments, it is proved that this method can guarantee the accuracy of unknown samples classification while reducing the time of cross-validation.
Starting Page	76
Ending Page	80
File Size	321048
Page Count	5
File Format	PDF
ISBN	9780769533117
DOI	10.1109/ISCID.2008.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hyperspectral sensors Optimization methods support vector machine (SVM) Independent component analysis cross-validation Data mining Support vector machines hyperspectral data independent component analysis (ICA) Support vector machine classification Signal processing Kernel mixture kernels Hyperspectral imaging Principal component analysis
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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