DocumentCode
2892130
Title
Feature Extraction and Selection in Ground Penetrating Radar with Experimental Data Set of Inclusions in Concrete Blocks
Author
Queiroz, F.A.A. ; Vieira, D.A.G. ; Travassos, X.L. ; Pantoja, M.F.
Author_Institution
Handcrafted Technol., ENACOM, Belo Horizonte, Brazil
Volume
2
fYear
2012
fDate
12-15 Dec. 2012
Firstpage
48
Lastpage
53
Abstract
Ground Penetrating Radar systems have been successfully used to access concrete structures conditions. Moreover, inclusions in concrete can be discriminated by simple models based on traces obtained by GPR. In this work, concrete blocks with different inclusions were probed in controlled conditions. Some features were extracted from Ascans of this experimental data set. To get efficient models, raw data were submitted to features selection and space reduction methods. Without complex data pre-processing, good accuracy and more explainable models with less computational burden were obtained.
Keywords
concrete; feature extraction; ground penetrating radar; radar imaging; A-scans; GPR; complex data preprocessing; concrete blocks inclusions; concrete structures condition access; experimental data set; feature extraction; feature selection; ground penetrating radar; space reduction methods; Concrete; Delay; Machine learning; Concrete; Ground Penetrating Radar; Iterative Search Margin Based Algorithm; Principal Components Analysis; k-Nearest Neighbor;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications (ICMLA), 2012 11th International Conference on
Conference_Location
Boca Raton, FL
Print_ISBN
978-1-4673-4651-1
Type
conf
DOI
10.1109/ICMLA.2012.139
Filename
6406724
Link To Document