In this paper we investigate random forest based language model adaptation. Large amounts of out-of-domain data are used to grow the decision trees while very small amounts of in-...
Random decision tree is an ensemble of decision trees. The feature at any node of a tree in the ensemble is chosen randomly from remaining features. A chosen discrete feature on a...
We present a system for estimating location and orientation of a person’s head, from depth data acquired by a low quality device. Our approach is based on discriminative random r...
Abstract. Watershed segmentation of spectral images is typically achieved by first transforming the high-dimensional input data into a scalar boundary indicator map which is used ...
An estimation of the generalization performance of classifier is one of most important problems in pattern clasification and neural network training theory. In this paper we estima...