@article {46228,
	title = {Small sample learning of superpixel classifiers for EM segmentation- extended version.},
	journal = {arXiv},
	year = {2014},
	month = {2014 Jun 6},
	pages = {arXiv:1406.1774 [cs.CV]},
	abstract = {<p>Pixel and superpixel classifiers have become essential tools for EM segmentation algorithms. Training these classifiers remains a major bottleneck primarily due to the requirement of completely annotating the dataset which is tedious, error-prone and costly. In this paper, we propose an interactive learning scheme for the superpixel classifier for EM segmentation. Our algorithm is "active semi-supervised" because it requests the labels of a small number of examples from user and applies label propagation technique to generate these queries. Using only a small set (\&lt;20\%) of all datapoints, the proposed algorithm consistently generates a classifier almost as accurate as that estimated from a complete groundtruth. We provide segmentation results on multiple datasets to show the strength of these classifiers.</p>
},
	url = {http://arxiv.org/abs/1406.1774},
	author = {Parag, Toufiq and Plaza, Stephen M and Scheffer, Louis K}
}
