Outlier mining of a vision sensing databasefor SVM regression improvement
作者： Wendy Flores-Fuentes , Daniel Hernandez-Balbuena , Julio C Rodriguez-Quiñonez , Daniel Olivas-Ugalde , Félix F González-Navarro
DOI: 10.1109/IECON.2015.7392101
关键词:
摘要: A 3D spatial measurement system has been enhanced by computational intelligence. The is based in opto-electronic scanning instrumentation for industrial task, robot navigation, medical scanning, and structural health monitoring applications. This paper presents new research performed the data processing of a vision sensing database. Multivariate outlier analysis implemented Mahalanobis distance order to improve Support Vector Machine (SVM) regression algorithm results. Measurement error used measurements correction. Demonstrating that optical systems present non-linear behavior could be positive impacted
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