Fault and gradient fault detection and reconstruction from scattered data
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Publication:2010357
DOI10.1016/j.cagd.2019.101786zbMath1505.65117OpenAlexW2981243384MaRDI QIDQ2010357
Alessandra Sestini, Cesare Bracco, Carlotta Giannelli, O. V. Davydov
Publication date: 27 November 2019
Published in: Computer Aided Geometric Design (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cagd.2019.101786
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Cites Work
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- Approximating scattered data with discontinuities
- Detection of discontinuities in scattered data approximation
- Minimal numerical differentiation formulas
- High order approximation to non-smooth multivariate functions
- Edge detection methods based on RBF interpolation
- Detecting and approximating fault lines from randomly scattered data
- Principal component analysis.
- The detection and recovery of discontinuity curves from scattered data
- Curve reconstruction from unorganized points
- Manifold approximation by moving least-squares projection (MMLS)
- Detecting derivative discontinuity locations in piecewise continuous functions from Fourier spectral data
- Error bounds for kernel-based numerical differentiation
- An application of numerical differentiation formulas to discontinuity curve detection from irregularly sampled data
- Polynomial Fitting for Edge Detection in Irregularly Sampled Signals and Images