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Table 2. Northern hemisphere temperatures - Posterior summaries for the parameters Multi-scale model AR(1) model
2001
Cited by 2
Table 1. Potential hydroelectric energy - Posterior summaries for the parameters Multi-scale model AR(1) model
Table 2. Northern hemisphere temperatures - Posterior summaries for the parameters Multi-scale model AR(1) model
Table 3. Reconstruction error at different multi-scale levels (Tleaf BP 100, q BP 5%).
in Multi-Scale Reconstruction of Implicit Surfaces with Attributes from Large Unorganized Point Sets
2004
"... In PAGE 9: ... Table3 shows the two error measures at 10 different lev- els compared to the highest resolution reconstruction for three models. Figures 10 and 11 show the visual quality of our multi- scale reconstruction method at different levels.... ..."
Cited by 1
Table 3: Observed speed-up for tree structure
"... In PAGE 14: ... The measured speed-up factors from the tests are presented in Table 3. Conclusions From Table 2 and Table3 we can see that configurations with up to 15 processors give a linear speed-up, which is very close to the number of processors used. For tests with 31 or... ..."
Table 1. Cost model in cycle for one-way comb implementation in the case of else if and switch structures. MpD depends on the decision tree structure, furthermore it is not a fixed constant for each cost function.
2004
"... In PAGE 6: ... An extra one cycle overhead is needed to pipeline predicate computations (comparisons) ahead of their qualified branches. The cycle costs for a one-way comb implementation, for the last leaf (worst latency) and for the median one are displayed in Table1 . The last leaf corresponds to the case where the targeted leaf is the last one in the comb therefore yielding to the maximum number of branch predictions for this decision tree.... In PAGE 7: ...difference is the number of integer comparisons per node, reduced to one. The cycle costs for a one-way comb implementation, are given in Table1 . Every cycle, only two... ..."
Cited by 1
Table 5: Relative error in estimating the performance of the tree structures.
"... In PAGE 18: ...67, - maximum number of entries in a node m = 126 or 84 or 50 (for B-trees, KDB-trees and R-trees, respectively). Table5 lists the relative errors of the actual results compared to the predictions of the proposed analytical models for the various data / query size combinations. Relative Error... ..."
Table 5: Relative error in estimating the performance of the tree structures.
"... In PAGE 17: ...67, - maximum number of entries in a node m = 126 or 84 or 50 (for B-trees, KDB-trees and R-trees, respectively). Table5 lists the relative errors of the actual results compared to the predictions of the proposed analytical models for the various data / query size combinations. Relative Error... ..."
Table 5: Relative error in estimating the performance of the tree structures.
"... In PAGE 17: ...67, - maximum number of entries in a node m = 126 or 84 or 50 (for B-trees, KDB-trees and R-trees, respectively). Table5 lists the relative errors of the actual results compared to the predictions of the proposed analytical models for the various data / query size combinations. Relative Error... ..."
Table 1. Performance comparison of image quality assessment models on LIVE JPEG/JPEG2000 database [13]. SS-SSIM: single-scale SSIM; MS-SSIM: multi-scale SSIM; CC: non-linear regression correlation coefficient; ROCC: Spearman rank-order correlation coefficient; MAE: mean absolute error; RMS: root mean squared error; OR: outlier ratio.
2003
Cited by 13
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