rTLsDeep: Post-Hurricane Damage Severity Classification from TLS and AI

Terrestrial laser scanning (TLS) data processing and post-hurricane damage severity classification at the individual tree level using deep Learning. Further details were published in Klauberg et al. (2023) <doi:10.3390/rs15041165>.

Version: 0.0.5
Depends: R (≥ 3.5.0)
Imports: caret, ggplot2, grDevices, lidR, keras, matrixStats, reticulate, rgl, sf, tensorflow
Suggests: terra, viridis
Published: 2023-03-31
Author: Carine Klauberg [aut], Ricardo Dalagnol [aut, cph], Matheus Ferreira [aut, ctb], Jason Vogel [aut, ctb], Caio Hamamura [aut, ctb, cre], Carlos Alberto Silva [aut, cph]
Maintainer: Caio Hamamura <caiohamamura at gmail.com>
BugReports: https://github.com/carlos-alberto-silva/rTLsDeep/issues
License: GPL-3
URL: https://github.com/carlos-alberto-silva/rTLsDeep
NeedsCompilation: no
Materials: NEWS
CRAN checks: rTLsDeep results

Documentation:

Reference manual: rTLsDeep.pdf

Downloads:

Package source: rTLsDeep_0.0.5.tar.gz
Windows binaries: r-devel: rTLsDeep_0.0.5.zip, r-release: rTLsDeep_0.0.5.zip, r-oldrel: rTLsDeep_0.0.5.zip
macOS binaries: r-release (arm64): rTLsDeep_0.0.5.tgz, r-oldrel (arm64): rTLsDeep_0.0.5.tgz, r-release (x86_64): rTLsDeep_0.0.5.tgz

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