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An MF is the optimal technique for TOA estimation, where a correlator template is matched exactly to the received signal.
In many TM techniques, instead of comparing a given template directly, a transformation of the template is matched with similar transformation of a candidate region using a similarity measure.
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A local face dataset (3500 different local faces) was presented to the system along with a common token and every local binary template was matched against every stolen template.
These templates were matched to tomograms of stained electron microscopy sections.
Finally, these view-specific templates are matched against the model of query actions.
For each frame, all sub-templates are matched to the target image individually, and the results of these sub-templates are then merged to obtain one consistent parameter transformation for the whole template.
If the number of templates for the target sample is larger and all these templates are matched one by one with the samples in images, the computation is very large and it is difficult to guarantee the speed of calculation.
PalmSecure technology uses a near-infrared light to capture a user's palm vein pattern, generating a unique biometric template that is matched against pre-registered users' palm vein patterns.
The shape templates generated are matched with shadow silhouettes.
Majority of tertiary structure of the template and query was matched in tertiary structure alignment.
This means that the gestural parameters calculated from the new movement input will be stored in a single, fixed-size buffer template, which can then be matched with the templates of the stored models (see Figure 7).
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