We show how improved sequences for magnetic resonance imaging can be found through optimization of Bayesian design scores. Combining approximate Bayesian inference and natural ima...
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann,...
This work investigates the use of nonlinear dependencies in natural image sequence statistics to learn higher-order structures in natural videos. We propose a two-layer model that...
In this paper, we present a novel method for human action recognition from any arbitrary view image sequence that uses the Cartesian component of optical flow velocity and human ...
This paper discusses the issues involved in implementing a dynamic programming algorithm for biological sequence comparison on a generalpurpose parallel computing platform based o...
W. S. Martins, Juan del Cuvillo, F. J. Useche, Kev...
Image-based location estimation methods typically recognize every photo independently, and their resulting reliance on strong visual feature matches makes them most suited for dis...