Sentence examples for models were learned from inspiring English sources

Accurate models were learned, which also make use of the relational aspects of a field plan, using information on the neighboring fields of a field, and the farming practices applied in it.

Spectral mixing models were learned from the training dataset and were used to regularize the image local smoothness.

Their models were complex and the parameters of their models were learned iteratively via greedy search.

Three separate Gibbs-sampled topic models were learned at the following topic resolutions: T = 500, T = 1000 and T = 2000 topics.

The relatively lower number of longer staying patients in the development cohort, upon which the GP models were learned, explains the higher uncertainty when predicting discharge in these patients.

We start by studying the statistics of natural images including the scale invariant properties, then generic prior models were learnt to duplicate the observed statistics.

Instead, we adopt CDPMs, where the models are learned from partially labelled images using Latent Support Vector Machines (LSVM).

Many previous approaches towards this end assume prior knowledge about the structure of activities, using which explicitly defined models are learned in a completely supervised manner.

Once generic deep models are learned from large-scale training sets, they can be applied to various crowd scenes without being trained again.

In [[70]], models are learned for nominal behaviors in the form of Gaussian Mixture Models.

The parameters of the models are learned jointly with the target of the specific task.