@article {5763,
	title = {JAABA: interactive machine learning for automatic annotation of animal behavior.},
	journal = {Nature Methods},
	volume = {10},
	year = {2013},
	month = {2012 Dec},
	pages = {64-7},
	abstract = {<p>We present a machine learning{\textendash}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.</p>
},
	issn = {1548-7091},
	author = {Kabra, Mayank and Robie, Alice A and Rivera-Alba, Marta and Branson, Steven and Branson, Kristin}
}
@proceedings {5767,
	title = {Learning animal social behavior from trajectory features.},
	year = {2012},
	month = {2012 Nov},
	address = {Tsukuba, Japan},
	author = {Eyjolfsdottir, Eyrun and Burgos-Artizzu, Xavier P. and Branson, Steven and Branson, Kristin and Anderson, David and Perona, Pietro}
}
