Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests Article Swipe
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Jörg Müller
,
Oliver Mitesser
,
H. Martin Schaefer
,
Sebastian Seibold
,
Annika Busse
,
Peter Kriegel
,
Dominik Rabl
,
Rudy Gelis
,
Alejandro Arteaga
,
Juan F. Freile
,
Gabriel Augusto Leite
,
Tomaz Nascimento de Melo
,
John G. LeBien
,
Marconi Campos‐Cerqueira
,
Nico Blüthgen
,
Constance J. Tremlett
,
Dennis Böttger
,
Heike Feldhaar
,
Nina Grella
,
Ana Falconí‐López
,
Jérôme Morinière
,
Zuzana Buřivalová
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.6084/m9.figshare.23620323
· OA: W4394288018
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.6084/m9.figshare.23620323
· OA: W4394288018
Raw data and R code to reproduce the analyses in the manuscript: Müller et al: Soundscapes and artificial intelligence provide powerful tools to track biodiversity recovery in tropical forests
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