We have previously proposed a trajectory model which is based on a mixture density network (MDN) trained with target variables augmented with dynamic features together with an algo...
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
An iterative model selection algorithm is proposed. The algorithm seeks relevant features and an optimal number of codewords (or codebook size) as part of the optimization. We use...
This paper presents a novel image-based approach to render plausible soft shadows for complex dynamic scenes with rectangular light sources. The algorithm's performance is mo...
In this paper, we present a novel method for estimating the effective number of independent variables in imaging applications that require multiple hypothesis testing. The method ...