Information fusion of a large number of sources with support vector machine techniques

Jerome J. Braun; Sunil P. Jeswani

doi:10.1117/12.486321

1 April 2003 Information fusion of a large number of sources with support vector machine techniques

Jerome J. Braun, Sunil P. Jeswani

Proceedings Volume 5099, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2003; (2003) https://doi.org/10.1117/12.486321
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Applications of information fusion include cases that involve a large number of information sources. Methods developed in the context of few information sources may not, and often do not, scale well to cases involving a large number of sources. This paper addresses specifically the problem of information fusion of large number of information sources. Performance of Support Vector Machine (SVM) based approach is investigated in input spaces consisting of thousands of information sources. Microarray pattern recognition, an important bioinformatics task with significant medical diagnostics applications, is considered from the information and sensor data fusion viewpoint, and recognition performance experiments conducted on microarray data are discussed. An approach involving high-dimensional input space partitioning is presented and its efficacy is investigated. The aspects of feature-level and decision-level fusion are discussed as well. The results indicate the feasibility of the SVM based information fusion with large number of information sources.

Citation Download Citation

Jerome J. Braun and Sunil P. Jeswani "Information fusion of a large number of sources with support vector machine techniques", Proc. SPIE 5099, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2003, (1 April 2003); https://doi.org/10.1117/12.486321

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available