Unsupervised improvement of visual detectors using cotraining Export

@misc{citeulike:1766855, abstract = {One significant challenge in the construction of visual detection systems is the acquisition of sufficient labeled data. This paper describes a new technique for training visual detectors which requires only a small quantity of labeled data, and then uses unlabeled data to improve performance over time. Unsupervised improvement is based on the cotraining framework of Blum and Mitchell, in which two disparate classifiers are trained simultaneously. Unlabeled examples which are confidently...}, author = {Levin, A. and Viola, P. and Freund, Y.}, citeulike-article-id = {1766855}, citeulike-linkout-0 = {http://citeseer.ist.psu.edu/701467.html}, citeulike-linkout-1 = {http://citeseer.lcs.mit.edu/701467.html}, citeulike-linkout-2 = {http://citeseer.ifi.unizh.ch/701467.html}, citeulike-linkout-3 = {http://citeseer.comp.nus.edu.sg/701467.html}, keywords = {cotraining, object-detection, semisupervised-learning, vision}, posted-at = {2007-10-14 15:40:26}, priority = {5}, title = {Unsupervised improvement of visual detectors using cotraining}, url = {http://citeseer.ist.psu.edu/701467.html}, year = {2003} }

TY - GEN ID - citeulike:1766855 L3 - citeulike-article-id:1766855 N2 - One significant challenge in the construction of visual detection systems is the acquisition of sufficient labeled data. This paper describes a new technique for training visual detectors which requires only a small quantity of labeled data, and then uses unlabeled data to improve performance over time. Unsupervised improvement is based on the cotraining framework of Blum and Mitchell, in which two disparate classifiers are trained simultaneously. Unlabeled examples which are confidently... TI - Unsupervised improvement of visual detectors using cotraining KW - cotraining KW - object-detection KW - semisupervised-learning KW - vision AU - Levin, A AU - Viola, P AU - Freund, Y PY - 2003/// UR - http://citeseer.ist.psu.edu/701467.html ER -