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We identify a series of metrics, and carry out extensive simulation studies on these metrics with different topological models and group member distributions for three case studies.
Therefore, it is convenient to compare the gain distribution of different metrics with different σ parameters.
Table 1 shows several performance metrics with different ε th on the optimal C values.
Table 3 shows several performance metrics with different ε th on the optimal σ values.
In this group, the performance metrics with different reserved channels are revealed.
Fig. 9 SR imaging with SNR 15, 10, 5, and 0 dB Fig. 10 Reconstruction metrics with different SNRs.
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The comparison was based on two metrics, with three different parameters each.
Using this approach, we pursue an experimental study designed to (a) gauge differences in plan quality metrics with respect to different tumor sites and different MIP treatment planning models, and (b) test the concept of critical-normal-tissue-ring a tissue ring of 5 mm thicritical-normal-tissue-ring aing target volume (PTV)—and its use for designing critical-normal-tissue-ring a
Fig. 4 The performance metrics of LSVM with different C values.
Fig. 5 The performance metrics of RBFSVM with different σ values.
Table 2 shows the performance of the proposed FR-PWN and NR-PWN metrics using images with different types of distortion as provided by the TID2008 database [22].
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determinants with different
arrangements with different
benchmarks with different
metrics with other
calculations with different
parameters with different
indicators with different
perspectives with different
determinations with different
criteria with different
metrics with long-term
metrics with negative
metrics with search-based
metrics with good
metrics with fixed
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