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The proposed method is evaluated by using four commonly-used datasets including two remote sensing images datasets, an indoor and outdoor scenes dataset, and a sports action dataset.
Based on the evaluation models, the performance of GPS SIS and BDS SIS is evaluated by using the measured data, respectively.
In the shape complementarity evaluation, the surface contact between proteins represented by the grid points is evaluated by using the score function of the contact surface area.
The likelihood of each hypothesis is evaluated by using optical flow information from the neighboring pixels.
The average SER is evaluated by using the Gauss-Chebyshev quadrature rule [23].
The traditional concept map assessment is evaluated by using criteria or via a human-based rubric.
The proposed mechanism is evaluated by using the EvalVid [13] framework.
This ratio is evaluated by using two values of the muon energy threshold.
The performance of the proposed corrosion descriptors is evaluated by using Fisher linear discriminant analysis (FLDA).
Then, the embedding distortion of the proposed methods is evaluated by using Lena as example image.
The effectiveness of the proposed filter is evaluated by using the simulation and real test experiment.
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