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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
DOI:10.32614/CRAN.package.rTLsDeep
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.html ,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, r-oldrel (x86_64):rTLsDeep_0.0.5.tgz

Linking:

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