In this paper we develop a system for human behaviour recognition in video sequences. Human behaviour is modelled as a stochastic sequence of actions. Actions are described by a f...
We propose a low cost method for the correction of the output of OCR engines through the use of human labor. The method employs an error estimator neural network that learns to as...
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
In this paper, we propose a multi-criteriabased active learning approach and effectively apply it to named entity recognition. Active learning targets to minimize the human annota...
Dan Shen, Jie Zhang, Jian Su, Guodong Zhou, Chew L...
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...