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Let HC x) be the confidence map produced by strong classifier in the early detecting period.
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Note that the confidence map is a binary matrix, in which the location of the movement turbulence is set to 0 and the location of the moving object is set to 1.
The confidence map is obtained as follows: we first estimate each pixel's probability density f(x ij ) using (5), then we decide which pixels belong to the movement turbulence and which ones belong to the moving object using an threshold θ.
Otherwise, we set it as 0. The obtained binary matrix is the final confidence map.
In a second step, object hypotheses are generated from the confidence maps by the competitive selection process described in Sect.
In this paper, an approach based on the confidence map and context information is proposed to robustly detect texts in natural scenes.
The grayscale value is 127 in the probability confidence map.
The fuzzy C-means (FCM) algorithm that combined with the trapezoidal forecasting model and the probability confidence map is adopted to improve the accuracy of road boundary detection.
How many serious discrepancies that are outside the confidence intervals on map reconstruction?
When the probability confidence map is used as the prediction model, the accuracy of SVM classifier cannot achieve 100%.
What has changed in the industry's road map is the growing confidence in new technologies that make electronic switches from single molecules or even single electrons.
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