CVNCQMSep 30, 2019

Deep learning tools for the measurement of animal behavior in neuroscience

arXiv:1909.13868v2389 citations
Originality Synthesis-oriented
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This work addresses the problem of efficiently measuring animal behavior for neuroscientists, but it is incremental as it reviews existing developments rather than introducing new methods.

The paper discusses the application of deep learning tools, particularly pose estimation, to measure animal behavior in neuroscience, highlighting recent advances that enable accurate, fast, and robust measurements.

Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capturing the postures of animals - pose estimation - has been rapidly advancing with new deep learning methods. While challenges still remain, we envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience.

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