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PARCS
Entry no. 55125
Comparing the accuracy of machine learning methods for classifying wild red deer behavior based on accelerometer data
Further info
http://www.parcs.ch/snp/pdf_public/2025/55125_20250311_132948_Bar-Geraetal._2025_Comparingtheaccuracyofmachinelearningmethodsforclassifyingwildreddeerbehaviorbasedonaccelerometerda.pdf
Private URL
-
External URL
https://doi.org/10.1186/s40317-025-00401-9
Datatype
Publication
Filename
-
Path
-
Alternative/Online Name
-
Author/Owner
Bar-Gera, B., Anderwald, P., Evans, A. L., Rempfler, T. & Signer, C.
Medium
File (digital)
Year created
2025
Month created
0
Location
-
Remarks
Acceleration data collected from wild red deer were used to train behavioral classification models. The most accurate model was able to differentiate between the behaviors lying, feeding, standing, walking, and running and can be used in future studies analyzing the behavior of wild red deer living in Alpine environments.
Ancestors
53626
Der Einfluss der Habitatqualität auf das Raum-Zeit-Verhalten beim Rothirsch (Cervus elaphus)
Project
Rempfler, T.
2020
Offspring
-