High‐resolution monitoring is fundamental to understand ecosystems dynamics in an era of
global change and biodiversity declines. While real‐time and automated monitoring of …

Deep neural networks (DNNs) are machine learning algorithms that have revolutionized
computer vision due to their remarkable successes in tasks like object classification and …

Abstract We propose a Cascaded Buffered IoU (C-BIoU) tracker to track multiple objects that
have irregular motions and indistinguishable appearances. When appearance features are …

Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural
activity across the brain. To understand the nature and function of these signals, we need …

Artificial intelligence (AI) is often used to describe the automation of complex tasks that we
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …

Understandings of the three-dimensional social behaviors of freely moving large-size
mammals are valuable for both agriculture and life science, yet challenging due to …

The first response exhibited by animals to changing environments is typically behavioral.
Behavior is thus central to predicting, and mitigating, the impacts that natural and …

Positive, prosocial interactions are essential for survival, development, and well-being.
These intricate and complex behaviors are mediated by an amalgamation of neural circuit …

Social signals can serve as potent emotional triggers with powerful impacts on processes
from cognition to valence processing. How are social signals dynamically and flexibly …

Contemporary pose estimation methods enable precise measurements of behavior via
supervised deep learning with hand-labeled video frames. Although effective in many cases …