Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA.
Nat Methods. 2013 Jan;10(1):64-7. doi: 10.1038/nmeth.2281. Epub 2012 Dec 2.
We present a machine learning-based system for automatically computing interpretable, quantitative measures of animal behavior. Through our interactive system, users encode their intuition about behavior by annotating a small set of video frames. These manual labels are converted into classifiers that can automatically annotate behaviors in screen-scale data sets. Our general-purpose system can create a variety of accurate individual and social behavior classifiers for different organisms, including mice and adult and larval Drosophila.
我们提出了一个基于机器学习的系统,用于自动计算可解释的、动物行为的定量指标。通过我们的交互系统,用户可以通过注释一小部分视频帧来表达他们对行为的直觉。这些手动标签被转换为分类器,可以自动注释屏幕尺度数据集的行为。我们的通用系统可以为不同的生物体(包括老鼠和成年及幼虫果蝇)创建各种准确的个体和社会行为分类器。