1-7 of 7
Keywords: Machine Learning
Close
Follow your search
Access your saved searches in your account

Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Journal Articles
Journal Articles
J Exp Biol (2024) 227 (23): jeb249201.
Published: 4 December 2024
... both energy expenditure and intake in 48 Adélie penguins ( Pygoscelis adeliae ) during the chick-rearing stage. We employed the machine learning algorithm random forest (RF) to predict accelerometry-derived metrics for feeding behaviour using depth data (our proxy for energy acquisition). We also built...
Includes: Supplementary data
Journal Articles
J Exp Biol (2024) 227 (14): jeb247457.
Published: 22 July 2024
... on feeding state, and not on sensory stimulation. Cuttlefish cognition Spectral profile Theta oscillations Principal component analysis Machine learning Chaire Beauté(s) PSL-L'Oréal Centre national de la recherche scientifique http://dx.doi.org/10.13039/501100004794...
Includes: Supplementary data
Journal Articles
J Exp Biol (2017) 220 (1): 25–34.
Published: 1 January 2017
... for automated analyses, video-based tracking algorithms for estimating the positions of interacting animals, and machine learning methods for recognizing patterns of interactions. These methods are extremely general in their applicability, and we review a subset of successful applications of them to biological...
Journal Articles
Journal Articles
J Exp Biol (2016) 219 (11): 1618–1624.
Published: 1 June 2016
...-logging devices (1.5–2.5 g) and use them to characterize behavior in two chipmunk species. We collected paired accelerometer readings and behavioral observations from captive individuals. We then employed techniques from machine learning to develop an automatic system for coding accelerometer readings...
Journal Articles
J Exp Biol (2014) 217 (24): 4295–4302.
Published: 15 December 2014
...’ (proxies for prey encounter used in other studies). The mean (±s.e.) number of prey captures per foraging trip was 446.6±66.28. By recording the behaviour of captive animals on HD video and using a supervised machine learning approach, we show that accelerometry signatures can classify the behaviour...