DocumentCode
875199
Title
Distributed sensor data fusion with binary decision trees
Author
Demirbas, Kerim
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, USA
Volume
25
Issue
5
fYear
1989
fDate
9/1/1989 12:00:00 AM
Firstpage
643
Lastpage
649
Abstract
A distributed sensor object recognition scheme that uses object features collected by several sensors is presented. Recognition is performed by a binary decision tree generated from a training set. The scheme does not assume the availability of any probability density functions, thus it is practical for nonparametric object recognition. Simulations have been performed for Gaussian feature objects, and some of the results are presented
Keywords
computerised pattern recognition; computerised picture processing; digital simulation; Gaussian feature objects; binary decision trees; computerised pattern recognition; computerised picture processing; digital simulation; distributed sensor object recognition; nonparametric object recognition; object features; training set; Computational modeling; Decision trees; Feature extraction; Fusion power generation; Infrared sensors; Object recognition; Probability density function; Sensor fusion; Sensor phenomena and characterization; Testing;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/7.42081
Filename
42081
Link To Document