DocumentCode
3333713
Title
Analysis of feature concatenation operation on vector spaces
Author
Özay, Mete ; Vural, Fatos T Yarman
Author_Institution
Bilgisayar Muhendisligi Bolumu, ODTU, Ankara, Turkey
fYear
2010
fDate
22-24 April 2010
Firstpage
1
Lastpage
4
Abstract
In this study, the theoretical and experimental analysis of feature space concatenation operation is introduced. This operation is widely used for data fusion and ensemble learning. Following the analysis, a new performance measure which is called Vectorization Measure (VM) is introduced. VM enables the estimation of the separability capacity of the fusion space by analyzing the sample margin distributions on the feature vector subpsaces.
Keywords
sensor fusion; vectors; data fusion; ensemble learning; feature space concatenation; vector spaces; vectorization measure; Art; Artificial neural networks; Biometrics; Face; Image classification; Kernel; Machine learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th
Conference_Location
Diyarbakir
Print_ISBN
978-1-4244-9672-3
Type
conf
DOI
10.1109/SIU.2010.5651471
Filename
5651471
Link To Document