Camera traps and deep learning enable efficient large‐scale density estimation of wildlife in temperate forest ecosystems

Abstract Automated detectors such as camera traps allow the efficient collection of large amounts of data for the monitoring of animal populations, but data processing and classification are a major bottleneck. Deep learning algorithms have gained increasing attention in this context, as they have t...

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Principais autores:	Maik Henrich, Christian Fiderer, Alisa Klamm, Anja Schneider, Axel Ballmann, Jürgen Stein, Raffael Kratzer, Rudolf Reiner, Sina Greiner, Sönke Twietmeyer, Tobias Rönitz, Volker Spicher, Simon Chamaillé‐Jammes, Vincent Miele, Gaspard Dussert, Marco Heurich
Format:	Artigo
Jezik:	Inglês
Izdano:	Wiley 2026-02-01
Serija:	Remote Sensing in Ecology and Conservation
Teme:	artificial intelligence Camera trap distance sampling European vertebrates photo classification species identification wildlife monitoring
Online dostop:	https://doi.org/10.1002/rse2.70030
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