DAMM for the detection and tracking of multiple animals within complex social and environmental settings.

ABSTRACT: Accurate detection and tracking of animals across diverse environments are crucial for behavioral studies in various disciplines, including neuroscience. Recently, machine learning and computer vision techniques have become integral to the neuroscientist's toolkit, enabling high-throughput behavioral studies. Despite advancements in localizing individual animals in simple environments, the task remains challenging in complex conditions due to intra-class visual variability and environmental diversity. These limitations hinder studies in ethologically-relevant conditions, such as when animals are concealed within nests or in obscured environments. Moreover, current tools are laborious and time-consuming to employ, requiring extensive, setup-specific annotation and model training/validation

SUBMITTER: Kaul G 

PROVIDER: S-EPMC10827216 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature