Sentence examples for fusion of knowledge from inspiring English sources

Fusion of knowledge of brain anatomy with intensity distribution information of CT brain image results in a unique solution for hemorrhage segmentation.

Fusion of knowledge elicitation and ontology learning techniques into ontology elicitation techniques can be interactively applied to automatically develop domain ontologies without involvement of a knowledge engineer.

There is a fusion of knowledge from various branches of science like pattern recognition methods, sensory technologies, chemo-metric tools and artificial intelligence in the construction of such systems.

The key ingredient, by far, was the enthusiastic collaboration of participants across missions, data sets, disciplines, and nations to produce a fusion of knowledge and experience focused on understanding the state of the Sun-Earth system during extreme space weather.

Studying collaboration patterns within and across disciplines or sciences contributes to understand the diversity of cooperative behaviors and fusion modes of knowledge.

The BN-BMLA extends the scope of local 'causal' discovery methods, and because of the direct interpretation of Bayesian posteriors, contrary to p-values from the frequentist-based approach, makes it an ideal candidate for creating probabilistic knowledge bases to support off-line meta-analysis and fusion of background knowledge.

MIT's motto is "mens et manus," or "mind and hand," signifying the fusion of academic knowledge with practical purpose.

Why it's still going The fusion of history, knowledge and manners speaks of gentler times and nobler ways, of humility, tweed, bicycle bells and feigned interest in the provenance of one's scrimshaw.

I discovered this painting.' The fusion of his knowledge in American art and my European art history background was the reason we were a good team and we could do a good job.

The analysis framework is based on the fusion of external knowledge, incorporated in a person and in a face classifier, and low-level features, clustered using temporal and spatial segmentation.

In fact, the computation of posterior distribution p ( x | y ), crucial for Bayesian restoration, can be seen as the DS fusion of the prior knowledge given by p ( x ) = p ( x 1 ) ∏ n = 2 N p ( x n | x n − 1 ) with the observation knowledge given by q ( x ) ∝ p ( y | x ) = Π n = 1 N p ( y n | x n ).