Parcs

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

Q:prjdatazoolungulateung_monitoringtelemetryreddeerbehaviourz_extmsc_bargeraprintout

Path

BarGera_et_al_2025_Animal_Biotelemetry.pdf

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

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.
Journal: Animal Biotelemetry

Ancestors

53626	Der Einfluss von Habitateigenschaften auf das Raum-Zeit-Verhalten beim Rothirsch (Cervus elaphus)	Project	Rempfler, T.	2020

53626

Der Einfluss von Habitateigenschaften auf das Raum-Zeit-Verhalten beim Rothirsch (Cervus elaphus)

Project

Rempfler, T.

2020

Offspring