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The performance comparison amongst various method based on the ON dataset is shown in Table 3.
Figure 11 Result of the automatic segmentation algorithm on dataset one.
In our experiments on dataset, affine gives the best results.
The accuracy of proposed model is 93.9% on dataset S1, 89.33% on S2 and 86.9% on dataset S3, respectively, applying 10-fold cross validation test.
In addition, empirical models were tuned based on dataset collected in situ.
It can be seen from Table 4 that the PLSA model yielded F-measure of 98.3% on dataset combination1 and 98.1% on dataset combination2.
Figure 10 Comparison between using four electrodes and using three electrodes on dataset IIa.
On dataset two, most of the fibers were also segmented correctly (Figure 14).
Figure 7 Comparison of method performances in the cross-validation on dataset IIb.
The results of parallel analysis on dataset STU are shown in Figure 1c, f.
Figure 1b, e present the abnormal results on dataset SALE in another way.
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