Evaluation of unsupervised learning algorithms for the classification of behavior from pose estimation data

Evaluation of unsupervised learning algorithms for the classification of behavior from pose estimation data

Summary: Analyzing animal behavior is crucial for decoding brain function, modeling neurological disorders, and assessing therapeutics. Recent advances in pose-estimation tools like DeepLabCut and SLEAP have revolutionized behavioral analysis by enabling precise tracking of animal body movements. Ho...

Full description

Saved in:
Bibliographic Details
Main Authors: Jakub Mlost, Rame Dawli, Xuan Liu, Ana Rita Costa, Iskra Pollak Dorocic
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Patterns
Subjects:
behavioral classification
unsupervised learning
neuroethology
neuroscience
Online Access:http://www.sciencedirect.com/science/article/pii/S2666389925000856
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items