Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Hidden Markov Models (HMM). We build our models on Principal Com...
Faisal I. Bashir, Wei Qu, Ashfaq A. Khokhar, Dan S...
Abstract. In this paper we describe the application of a novel statistical videomodeling scheme to sequences of multiple sclerosis (MS) images taken over time. The analysis of the ...
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...