Cargando…
The use of an unsupervised learning approach for characterizing latent behaviors in accelerometer data
The recent increase in data accuracy from high resolution accelerometers offers substantial potential for improved understanding and prediction of animal movements. However, current approaches used for analysing these multivariable datasets typically require existing knowledge of the behaviors of th...
Autores principales: | Chimienti, Marianna, Cornulier, Thomas, Owen, Ellie, Bolton, Mark, Davies, Ian M., Travis, Justin M.J., Scott, Beth E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739568/ https://www.ncbi.nlm.nih.gov/pubmed/26865961 http://dx.doi.org/10.1002/ece3.1914 |
Ejemplares similares
-
Taking movement data to new depths: Inferring prey availability and patch profitability from seabird foraging behavior
por: Chimienti, Marianna, et al.
Publicado: (2017) -
Modelling foraging movements of diving predators: a theoretical study exploring the effect of heterogeneous landscapes on foraging efficiency
por: Chimienti, Marianna, et al.
Publicado: (2014) -
Applications of Accelerometers and Other Bio-Logging Devices in Captive and Wild Animals
por: Campera, Marco, et al.
Publicado: (2023) -
Segmenting accelerometer data from daily life with unsupervised machine learning
por: van Kuppevelt, Dafne, et al.
Publicado: (2019) -
Latent space unsupervised semantic segmentation
por: Strommen, Knut J., et al.
Publicado: (2023)