Boosting classification performance via data fusion

Costin Barbu; Jing Peng

doi:10.1109/RADAR.2015.7131102

Boosting classification performance via data fusion

Costin Barbu, Jing Peng

Computer Science

Research output: Contribution to journal › Conference article › peer-review

Abstract

An engine for fusing data from multiple sensors for classification is provided in this paper. Two novel methods for fusing multiple representations of data with boosting are presented and empirically evaluated against other fusion techniques as candidate algorithms for the fusion engine. We argue that information fusion from sensors operating in complementary regions of the spectrum and/or spatially separated can improve the classification performance.

Original language	English
Article number	7131102
Pages (from-to)	783-787
Number of pages	5
Journal	IEEE National Radar Conference - Proceedings
Volume	2015-June
Issue number	June
DOIs	https://doi.org/10.1109/RADAR.2015.7131102
State	Published - 22 Jun 2015
Event	2015 IEEE International Radar Conference, RadarCon 2015 - Arlington, United States Duration: 10 May 2015 → 15 May 2015

Keywords

boosting
classification
data fusion
radar

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10.1109/RADAR.2015.7131102

Cite this

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title = "Boosting classification performance via data fusion",

abstract = "An engine for fusing data from multiple sensors for classification is provided in this paper. Two novel methods for fusing multiple representations of data with boosting are presented and empirically evaluated against other fusion techniques as candidate algorithms for the fusion engine. We argue that information fusion from sensors operating in complementary regions of the spectrum and/or spatially separated can improve the classification performance.",

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AB - An engine for fusing data from multiple sensors for classification is provided in this paper. Two novel methods for fusing multiple representations of data with boosting are presented and empirically evaluated against other fusion techniques as candidate algorithms for the fusion engine. We argue that information fusion from sensors operating in complementary regions of the spectrum and/or spatially separated can improve the classification performance.

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KW - data fusion

KW - radar

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DO - 10.1109/RADAR.2015.7131102

M3 - Conference article

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Y2 - 10 May 2015 through 15 May 2015

ER -

Boosting classification performance via data fusion

Abstract

Keywords

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