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The problem for T-Mobile, though, is the dwindling number of people still using feature phones.
Landmarks are extracted using feature detectors.
Moreover, this approach allows using feature vectors in different sizes.
We tested unsupervised classification on both databases using feature F1.
Table 3 shows the results of using feature selection.
Using feature differencing is faster for two reasons.
Therefore, we can effectively improve classification efficiency using feature selection.
Solutions can be devised by using feature space organization approaches.
Stereo matching using feature vectors has two difficulties.
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Images were analyzed using Feature Extraction software (Agilent Technologies) version 8.1.
Images provided by the scanner were analyzed using Feature Extraction software v10.7 (Agilent Technologies).
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