Exact(5)
The seductive risk of a tontine is one of its defining features — a feature that may sorely be needed today, for entirely different reasons.
Combining the LBP and HOG features, a feature vector of size 1 × 1770 is obtained for each image window.
Besides, to alleviate redundancy of high-dimensional convolutional features, a feature selection method is adopted, which can reduce computation complexity and improve tracking accuracy.
Besides, to alleviate the redundancy from high-dimensional convolutional features, a feature selection method is adopted to remove noisy and irrelevant feature maps, which can reduce computation redundancy and improve tracking accuracy.
Concatenating the MV and ILD/IPD features, a feature vector can be obtained at each T-F unit, which is (widetilde {mathbf {u}}left ({m,f} right) = {left [ {{{mathbf {widehat {z}}}^{T}}left ({m,f} right),alpha left ({m,f} right),phi left ({m,f} right)} right ]^{T}} in {mathbb {R}^{6}}).
Similar(55)
Thus, to emphasize the importance of sensitive features, a feature-weighting step is needed to guarantee a more accurate classification result.
According to a report from The Wall Street Journal, Google Maps will soon be releasing a walking-focused augmented reality (AR) feature -- a feature that reporter David Pierce was able to demo firsthand.
There are two types of dependency: requires, when feature A requires feature B, an application that contains feature A also has to include feature B; and excludes, when feature A excludes feature B, no application may include both features.
A feature (Feature A) seen around 115°W, 10°S in Fig. 8a is not shifted in Fig. 8b d (meaning that Feature A is moving westward at 80 m s−1).
Decomposing a complex shape into shape features is a feature recognition problem.
The system was optimized by eliminating unimportant features using a feature selection method (UTA method).
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Justyna Jupowicz-Kozak
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