Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
We have established a novel control system for combining the parallel execution of deterministic and non-deterministic medical imaging applications on a single platform, sharing t...
This work presents a Log-stable model for natural images blockvariance. Exponential and halfnormal distributions have been previously used to model block-variance, but they were e...
Spatially-correlated intra-die process variations result in significant core-to-core frequency variations in chip-multiprocessors. An analytical model for frequency island chip-mu...
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...