Unsupervised behaviour analysis and magnification (uBAM) using deep learning

Biagio Brattoli, Uta Büchler, Michael Dorkenwald, Philipp Reiser, Linard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Björn Ommer

Abstract: Being able to precisely analyse behaviour is essential for the study of motor behaviour in health and disease, but is often time- and labour-intensive. Brattoli et al. develop an automatic approach based on deep learning for analysing motor behaviour and evaluate it on different species and diverse motor functions.