For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
Discriminative reranking has been able to significantly improve parsing performance, and co-training has proven to be an effective weakly supervised learning algorithm to bootstr...
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is g...
Color calibration is a time-consuming, and therefore costly requirement for most robot teams at RoboCup. This paper presents an approach for autonomous color learning on-board a mo...
Many recognition algorithms depend on careful positioning of an object into a canonical pose, so the position of features relative to a fixed coordinate system can be examined. Cu...