Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.
Version: 0.7.2 Imports: png, neuralnet, raster, Rcpp, MASS, grDevices, graphics, stats, shiny LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat Published: 2024-05-08 DOI: 10.32614/CRAN.package.trackdem Author: Marjolein Bruijning, Marco D. Visser, Caspar A. Hallmann, Eelke Jongejans Maintainer: Marjolein Bruijning <m.bruijning at uva.nl> BugReports: https://github.com/marjoleinbruijning/trackdem/issues License: GPL-2 URL: https://github.com/marjoleinbruijning/trackdem NeedsCompilation: yes SystemRequirements: Python (>=2.7), Libav, ExifTool Citation: trackdem citation info In views: SpatioTemporal, Tracking CRAN checks: trackdem results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=trackdem to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4