| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| artigo principal | 162 B | Microsoft Word XML |
Advisor(s)
Abstract(s)
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.
Description
Keywords
Behavioural methods Experimental organisms Machine learning
Citation
Kabra, M., Robie, A. A., Rivera-Alba, M., Branson, S., Branson, K. (2013). JAABA: interactive machine learning for automatic annotation of animal behavior. Nat Meth, 10(1), 64–67.