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Table 7 Confusion matrix for the thermal image classifier (3 types) (t1: sedan, t2: SUV, t3:truck) Classified t1 t2 t3 Actual t1 126 16 16 t2 26 8 2 t3 26 4 12 Table 8 Accuracy of vehicle classification by the thermal image classifier (3 types) Type The number of vehicle image Correct Accuracy t1 214 186 86.9 t2 36 8 22.2 t3 42 12 28.6 Overall 292 292 70.5.
Table 5 Confusion matrix for the visual image classifier (3 types) (t1: sedan, t2: SUV, t3:truck) Classified t1 t2 t3 Actual t1 155 4 2 t2 3 114 3 Table2 108 Table 6 Accuracy of vehicle classification by the visual image classifier (3 types) Type The number of vehicle image Correct Accuracy t1 161 155 96.3 t2 120 114 95.0 t3 110 108 98.2 Overall 391 391 96.4.
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This resulted in an image corrected for atmospheric scattering.
b The same image corrected for the background bias.
AC1 Each PET image corrected by its corresponding CT-derived attenuation map.
(a) Axial, coronal, and sagittal views of the baseline PET image, corrected with the MR atlas without signal void.
On bottom: pixel-by-pixel difference between the same image corrected with conventional flat fielding (not reported).
After correction using the proposed MAR, a high activity uptake is visible in the same region, while the image corrected using the Siemens MAR technique remains unchanged.
Activities in the VOIs were measured in the images corrected with different attenuation maps.
Figure 4 SPECT images corrected for attenuation and scatter using TCT and CT attenuation maps.
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