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The sparse vector field consensus (SparseVFC) algorithm (Ma et al., 2013 <doi:10.1016/j.patcog.2013.05.017>) for robust vector field learning. Largely translated from the Matlab functions in <https://github.com/jiayi-ma/VFC>.
Version: | 0.1.2 |
Depends: | R (≥ 4.1.0) |
Imports: | pdist, purrr |
Suggests: | ggplot2, dplyr, tibble, rmarkdown, grid, knitr |
Published: | 2023-11-09 |
DOI: | 10.32614/CRAN.package.SparseVFC |
Author: | Jingmeng Cui |
Maintainer: | Jingmeng Cui <jingmeng.cui at outlook.com> |
BugReports: | https://github.com/Sciurus365/SparseVFC/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/Sciurus365/SparseVFC |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | SparseVFC results |
Reference manual: | SparseVFC.pdf |
Vignettes: |
demo |
Package source: | SparseVFC_0.1.2.tar.gz |
Windows binaries: | r-devel: SparseVFC_0.1.2.zip, r-release: SparseVFC_0.1.2.zip, r-oldrel: SparseVFC_0.1.2.zip |
macOS binaries: | r-release (arm64): SparseVFC_0.1.2.tgz, r-oldrel (arm64): SparseVFC_0.1.2.tgz, r-release (x86_64): SparseVFC_0.1.2.tgz, r-oldrel (x86_64): SparseVFC_0.1.2.tgz |
Old sources: | SparseVFC archive |
Reverse imports: | fitlandr |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.