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| artigo principal | 162 B | Microsoft Word XML |
Orientador(es)
Resumo(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.
Descrição
Palavras-chave
Behavioural methods Experimental organisms Machine learning
Contexto Educativo
Citação
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.
Editora
Nature Publishing Group