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Tsai et al. [16] propose expressing a level set function as a parametric combination of the principle components from a set of training shapes.
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C4.5 builds decision trees from a set of training data.
We present a novel method for automatic shape model building from a collection of training shapes.
Let us f i is a set of training images and g i is generated from the 2D Gaussian shape; then, H_{i}^ = frac{{G_{i} }}{{F_{i} }}, (2 where the division is performed element-wise.
The parameters of these distributions are estimated from a set of examples, the training set.
To restrict the segmentation to a set of admissible liver shapes, a shape database is compiled, from which any new liver shape is expressed by a set of parameters called modes of variation.
Morphological shape design is interpreted in this paper as a search for new shapes from a particular application domain represented by a set of selected shape instances.
This table is from a set of experiments or examples, collected as the training data set.
A statistical shape model of the head is created from a set of 100 MRI scans.
Eight subjects were scanned on a pair recognition task before, during and after a 2-week training period when subjects learned to recognize a set of shape pairs.
In the present study, we used a set of parametrically designed shape stimuli (Fig. 1) and conducted single-cell recordings from the inferotemporal cortex in two different training histories: after fine-discrimination training and after experiencing only coarse discrimination.
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