Use 'BirdNET', a state-of-the-art deep learning classifier, to automatically identify (bird) sounds. Analyze bioacoustic datasets without any computer science background using a pre-trained model or a custom trained classifier. Predict bird species occurrence based on location and week of the year. Kahl, S., Wood, C. M., Eibl, M., & Klinck, H. (2021) <doi:10.1016/j.ecoinf.2021.101236>.
| Version: | 0.3.2 |
| Depends: | R (≥ 4.0) |
| Imports: | reticulate (≥ 1.41) |
| Suggests: | arrow,curl,devtools,knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2025-04-30 |
| DOI: | 10.32614/CRAN.package.birdnetR |
| Author: | Felix Günther [cre], Stefan Kahl [aut, cph], BirdNET Team [aut] |
| Maintainer: | Felix Günther <felix.guenther at informatik.tu-chemnitz.de> |
| BugReports: | https://github.com/birdnet-team/birdnetR/issues |
| License: | MIT + fileLICENSE |
| URL: | https://birdnet-team.github.io/birdnetR/,https://github.com/birdnet-team/birdnetR |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | birdnetR results |
| Reference manual: | birdnetR.html ,birdnetR.pdf |
| Vignettes: | Troubleshoot (source,R code) Get started with birdnetR (source,R code) |
| Package source: | birdnetR_0.3.2.tar.gz |
| Windows binaries: | r-devel:birdnetR_0.3.2.zip, r-release:birdnetR_0.3.2.zip, r-oldrel:birdnetR_0.3.2.zip |
| macOS binaries: | r-release (arm64):birdnetR_0.3.2.tgz, r-oldrel (arm64):birdnetR_0.3.2.tgz, r-release (x86_64):birdnetR_0.3.2.tgz, r-oldrel (x86_64):birdnetR_0.3.2.tgz |
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