Sentence examples for exemplar learning from inspiring English sources

The result is that non-experts learn from single examples (Gregan-Paxton 2001), leading to exemplar learning (Barsalou 1991) and single category beliefs (Rajagopal and Burnkrant 2009).

Thus, it cannot completely be excluded that previous results are based on exemplar learning rather than on abstract rule establishment.

Below are the two exemplars of learning artifacts created by Sketchbook. Figure 5 depicts a process of bean growth.

For each unique exemplar, subjects learned an age, location, and usage/occupation fact (e.g., "the gilbert building is forty-five years old"; "the gilbert building is located in baton rouge"; "the gilbert building is used for community meetings").

They used these exemplars to learn patterns in the testimony.

In a nutshell, RESPECT is all about learning from exemplar teachers and principals.

The approaches are based on learning from exemplars, clustering and the use of Bayesian network classifiers.

Further, even though they are based on learning from exemplars, they are not ontology specific; i.e. they do not assume the use of any particular ontology.

These results imply a predominance of the learned irrelevance mechanism even when any direct transfer of learning about exemplars in the pre-shift phase is precluded.

Of most interest, before and after studying the exemplars, participants made category learning judgments (CLJs), which involved predicting the likelihood of correctly classifying novel birds into each family.

In this paper, we propose a vehicle detection framework, which combines Deep Convolutional Neural Network (DNN) based feature learning with Exemplar-SVMs (E-SVMS) based, robust instance classifier to achieve robust vehicle detection in satellite images.