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Template-based methods make direct comparisons between a test pattern and the templates of training data via dynamic time warping (DTW), and potentially they can capture the speech dynamics better than HMMs.
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In template selection, the goal is to choose a small subset of templates as the representatives for the full set of training templates.
An advantage of Rolexa is that it does not depend on supervised learning, thereby eliminating the need to resequence known templates for training and thereby increasing overall yield.
Until recently, template-based methods had been impractical for large tasks of speech recognition, since feature vectors of training templates need to be stored in computer memory.
Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria.
On the other hand, some ATR approaches [8, 1, 9] depend on the use of multi-view exemplar templates to train a classifier.
The execution of an experimental study with all twelve templates found would be costly, since the use of each template requires a lot of training and is time consuming.
The European Training Curriculum for Radiology (former European Training Charter for Clinical Radiology) of the ESR is designed to provide a valuable template for training radiologists and to enhance the quality of care for patients throughout Europe [16].
It can function alone, as a reference-free particle picker with the unique ability to sort particles based on size, or it can also be used as a way to bootstrap the creation of templates or training datasets for other particle pickers.
They identified the potential value of training courses, templates or 'toolkits'toolkits
Our main work focuses on training templates of noise reduction and edge detection CNNs.
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