### Table 6 Multiplierless 32d QMF filter banks found by DLM with static and adaptive weightsa

1998

"... In PAGE 23: ...ll the coe cients to be 0.9474. After multiplying each coe cient by this scaling factor and restricting each coe cient to a PO2 form with a maximum of 6 ONE bits, we apply DLM with both static and dynamic weights to find the best PO2 designs. Table6 compares the objectives of the designs found and the corresponding convergence times of DLM. Using the adaptive DLM, all the searches con- verge, and most designs have better reconstruction errors.... ..."

### TABLE II PROJECTION ALGORITHM FOR CONSISTENT RECONSTRUCTION FROM A QMP REPRESENTATION

1998

Cited by 63

### Table 1: Results of alpha-solid reconstruction. The table show for each object, from left to right: (1) The number of points in the sampling; (2) The time, in minutes, required by the alpha-solid computation (including 3D Delaunay triangulation, computation of family of alpha-shapes, automatic selection of alpha value, improvement by local sculpturing). All computations were carried out on a SGI Indigo2, with a 250MHz MIPS 4400 CPU; (3) The number of tetrahedra in the initial alpha-solid; (4) The number of tetrahedra removed by the heuristic; (5) The number of triangles in the boundary of the nal reconstructed model.

1999

"... In PAGE 20: ... The depth of such look-ahead search can be limited, for all practical purposes, to a small integer value (we have used 10 for all our examples).Figures 16, 17 and 18 and Table1 illustrate some examples of alpha-solids computed with the tech- nique described above. 7 Mesh Simpli cation Surface mesh simpli cation refers to a general cat- egory of techniques designed to generate compact, adaptive approximations of dense tesselated sur- faces.... ..."

Cited by 28

### Table 2: RMS and maximum errors for reconstruction of the calibration object using the optimal forward projection and the optimal backward projection.

2003

"... In PAGE 20: ... The measured fiducial points centroids and projector stripe ids are shown as a reference. Table2 shows the RMS and the maximum reconstruction errors of the calibration object in five tests with random camera and projector locations. Two cases are studied: 1) when the camera and the projector matrices are obtained by minimizing the forward projection error and 2) when the camera and the projector matrices are obtained by minimizing the backward projection error.... ..."

### Table 1: Results of alpha-solid reconstruction. The table show for each object, from left

"... In PAGE 20: ... The depth of such look-ahead search can be limited, for all practical purposes, to a small integer value #28wehave used 10 for all our examples#29. Figures 16, 17 and 18 and Table1 illustrate some examples of alpha-solids computed with the tech- nique described above. 7 Mesh Simpli#0Ccation Surface mesh simpli#0Ccation refers to a general cat- egory of techniques designed to generate compact, adaptive approximations of dense tesselated sur- faces.... ..."

### Table 1: Results of alpha-solid reconstruction. The table shows for each object, from left to right: (1) The number of points in the sampling; (2) The time, in minutes, required by the alpha-solid computation (including 3D Delaunay triangulation, computation of family of alpha-shapes, automatic selection of -value, improvement by local sculpturing). All computations were carried out on a SGI Indigo2, with a 250MHz MIPS 4400 CPU; (3) The number of tetrahedra in the initial alpha-solid; (4) The number of tetrahedra removed by the heuristic; (5) The number of triangles in the boundary of the nal reconstructed model.

1997

"... In PAGE 2: ... However, we apply the iterative removal of tetrahedra only to locally im- prove the alpha-solid, rather than as a global strategy to extract an interpolating mesh from the 3D Delaunay trian- gulation. Figure 2 and Table1 illustrate some examples of alpha-solids computed with the technique described above. 4 Mesh Simpli cation Surface mesh simpli cation refers to a general category of techniques designed to generate compact, adaptive approx- imations of dense tessellated surfaces.... ..."

Cited by 10

### Table 3: Errors in reconstructing the bubble shape and esti- mating the void fraction from the reconstructed images. See text for explanation of the models.

"... In PAGE 6: ... 4 shows examples of the image reconstruction results. Table3... In PAGE 7: ... With the proposed approach such goal variables can be estimated directly without explicit re- construction of the image. The last column in Table3 shows the relative absolute error in estimating the void fraction di- rectly from the projections of the potential signals. With Bayesian methods we can easily calculate confidence intervals for outputs.... ..."

### Table 3: Errors in reconstructing the bubble shape and esti- mating the void fraction from the reconstructed images. See text for explanation of the models.

"... In PAGE 6: ... 4 shows examples of the image reconstruction results. Table3... In PAGE 7: ... With the proposed approach such goal variables can be estimated directly without explicit re- construction of the image. The last column in Table3 shows the relative absolute error in estimating the void fraction di- rectly from the projections of the potential signals. With Bayesian methods we can easily calculate confidence intervals for outputs.... ..."

### Table 5: Errors in reconstructing the bubble shape and estimating the void fraction from the reconstructed images. See text for explanation of the models. Method Classification error

2001

"... In PAGE 17: ... 8 shows examples of the image reconstruction results. Table5 shows the quality of the image reconstruc- tions, measured by the error in the void fraction and the percentage of erroneous pixels in the segmentation, over the test set. An important goal in this process tomography application was to estimate the void fraction, which is the proportion of gas and liquid in the image.... In PAGE 17: ... With the proposed approach such goal variables can be estimated directly without explicit reconstruction of the image. The last column in Table5 shows the relative absolute error in estimating the void fraction directly from the projections of the potential signals. In solving real problems with non-linear learning models the ability to assess the confidence of the output is necessary.... ..."

Cited by 12

### Table 5: Errors in reconstructing the bubble shape and estimating the void fraction from the reconstructed images. See text for explanation of the models. Method Classification error

2001

"... In PAGE 17: ... 8 shows examples of the image reconstruction results. Table5 shows the quality of the image reconstruc- tions, measured by the error in the void fraction and the percentage of erroneous pixels in the segmentation, over the test set. An important goal in this process tomography application was to estimate the void fraction, which is the proportion of gas and liquid in the image.... In PAGE 17: ... With the proposed approach such goal variables can be estimated directly without explicit reconstruction of the image. The last column in Table5 shows the relative absolute error in estimating the void fraction directly from the projections of the potential signals. In solving real problems with non-linear learning models the ability to assess the confidence of the output is necessary.... ..."

Cited by 12