### Table 1: Model-based segmentation and visualization

"... In PAGE 8: ... As a simple example, colors and transparencies of such objects should be selected such that contrasts are easily perceived and all relevant objects are sufficiently visible. Comparison of Model-based Segmentation and Visualization In Table1 , we compare information used for model-based segmentation and visualization. Table 1: Model-based segmentation and visualization... ..."

### Table 3. Performance of the model-based segmenter

2000

Cited by 25

### Table 3. Performance of the model-based segmenter

2000

Cited by 25

### Table 4 ARMD trial

2007

"... In PAGE 17: ...ared. For the observed, partially incomplete data, GEE is supplemented with WGEE. Further, a random-intercepts GLMM is considered, based on numerical integration. The GEE analyses are reported in Table4 and the random-effects models in Table 5. For GEE, a working exchangeable correlation matrix is considered.... In PAGE 19: ... The advantage of having separate treatment effects at each time is that particular attention can be given at the treatment effect assessment at the last planned measurement occasion, that is, after one year. From Table4 it is clear that the model-based and empirically corrected standard errors agree extremely well. This is due to the unstructured nature of the full time by treatment mean structure.... In PAGE 20: ... The results for the random-effects models are given in Table 5. We observe the usual relationship between the marginal parameters of Table4 and their random-effects counterparts. Note also that the random-intercepts variance is largest under LOCF, underscoring again that this method artificially increases the association between mea- surements on the same subject.... ..."

### Table 9: List of Model-based tools and methodologies and references to these tools

"... In PAGE 8: ...nderstanding and modifying the web application ........................................................... 70 Table9 : List of Model-based tools and methodologies and references to these tools .... ..."

### Table 2. Optimal views based on model-based reconstruction.

2004

"... In PAGE 5: ... Based on an average reconstruction time of 30 sec- onds, this search takes about 45 hours. The results are presented in Table2 which shows the optimal views for K = {1,2,3,4,5} and the correspond- ing minimum average reconstruction errors (refer to Table 1 Figure 7. Reconstruction errors for all view con- figurations with 4 cameras (K = 4) ranked by magnitude of ensemble error.... In PAGE 5: ... Figure 7 shows the errors of all combinatorial view configurations for the case K = 4, ranked in ascending order of error. Each er- ror bar represents the subjects standard deviation for that configuration (the first error bar corresponds to the optimal configuration and is the subject standard deviation listed in Table2 ). Other plots for K = 1,2,3 and 5 are quite sim- ilar in nature, all showing a well-defined minimum with the subject variation (error-bars) being lowest for the best configuration (left most) and highest for the worst (right most).... In PAGE 5: ... Using the same search strategy, we now evaluate the visual hull constructions ob- tained from the given subset of silhouette images and com- pare them to the ground truth. Table 3 shows the optimal views for K = {2,3,4,5} and the corresponding error val- ues (same format as in Table2 except that the visual hull from a single silhouette (K = 1) has no finite volume and... In PAGE 6: ... There are a few dif- ferences but these are somewhat misleading. The best view configurations in Table2 are marked in Figure 8 with ar- rows. We note that our model-based optimal views have al- most the same errors as the best views chosen with visual hull method and are always in the first plateau or top quar- tile that includes the key profile view #10.... ..."

Cited by 7

### Table 4: Comparison with model-based clustering using the EM algorithm.

1997

Cited by 17

### Table 2: Summary of predictive model-based schemes described.

1998

"... In PAGE 13: ... In addition, iterative schemes must be used to estimate the multiple components once the corrupted-speech observations have been generated. 6 Summary of Techniques Table2 goes here The techniques presented in the previous sections are summarised in table 2. The table gives; the technique, the nal form of the corrupted-speech model for each speech and noise pairing, the domain it is normally applied in, the features that may be compensated, the model parameters that may be compensated, and the computational cost of the technique13.... ..."

Cited by 10

### TABLE V SEQUENTIAL MODEL-BASED FAULT DIAGNOSIS

2005

Cited by 10