?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
We examine the verification of simple quantifiers in natural language from a computational model perspective. We refer to previous neuropsychological investigations of the same pr...
This paper focuses on the Cyclops64 computer architecture and presents an analytical model and performance simulation results for the preloading and loop unrolling approaches to op...
Yanwei Niu, Ziang Hu, Kenneth E. Barner, Guang R. ...
This work presents a novel approach in automatic detection of the lung nodules and is compared with respect to parametric nodule models in terms of sensitivity and specificity. A ...
Amal A. Farag, James Graham, Salwa Elshazly, Aly F...
We develop a module-based framework for constraint modeling where it is possible to combine different constraint modeling languages and exploit their strengths in a flexible way. ...