2015
DOI: 10.1109/tim.2015.2418684
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An Adaptive Support Vector Machine-Based Workpiece Surface Classification System Using High-Definition Metrology

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Cited by 49 publications
(12 citation statements)
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“…Different levels of noise have been added in the testing signals to check the robustness of the proposed algorithm. The performance of the SR‐ELM classifier has been compared with the multiclass SVM, adaptive SVM, and PNN.…”
Section: Introductionmentioning
confidence: 99%
“…Different levels of noise have been added in the testing signals to check the robustness of the proposed algorithm. The performance of the SR‐ELM classifier has been compared with the multiclass SVM, adaptive SVM, and PNN.…”
Section: Introductionmentioning
confidence: 99%
“…Feature recognition is to extract and recognize form features of a three-dimensional (3D) computer-aided design (CAD) part model. The feature recognition results are helpful to product designing, 13 process planning, 410 and numerical control (NC) programming. 1117 Thus, it is regarded as the premier technic for the integrated representation of product lifecycle data.…”
Section: Introductionmentioning
confidence: 99%
“…Several researches about online controlling flat surface variation based on HDM have been conducted. Du et al [2][3][4] proposed a shearletbased method and support vector machine-based methods to separate and extract different surface components using HDM. Du and Fei [5] also presented a co-Kriging method based on multivariate spatial statistics to estimate surface form error using HDM.…”
Section: Introductionmentioning
confidence: 99%