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The experimental results show that our methods achieve a better time and load balancing results.
The results show that both methods achieve a similar geometric result.
Both the proposed re-parameterization methods achieve a good degree of output prediction at a greatly decreased computational cost.
These methods achieve a high accuracy with a very short calibration time estimated to about 10 clock cycles.
Our numerical results demonstrate that the new methods achieve a near constant false alarm rate behavior in contrast to earlier approaches from the literature.
Similar to the behavior observed for the Intel-Berkeley data, MC again reaches a performance plateau while the other methods achieve a monotonically reducing reconstruction error.
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As shown in Figure 11, the proposed methods achieved a high overall accuracy and the highest precision rates.
Having previously only used spray paint in designs, where few colors were available, ColorOrgy now employs predominately brush methods, achieving a smooth finish with a spray gun.
As a result, the methods achieved a satisfactory overall success rate.
It is noteworthy that none of the methods achieved a mean tree FP less than 0.95.
Results showed that these methods achieved a MAE of 18.5 19.7% on CB502 dataset.
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