Hybrid distribution combinations results of PPSM model using miscellaneous images of MSRC, BSDS, and COCO datasets
| PPSM joint distributions | MSRC | BSDS | COCO | |||
|---|---|---|---|---|---|---|
| # of best segmented images | Best performance (%) | # of best segmented images | Best performance (%) | # of best segmented images | Best performance (%) | |
| Gaussian | 1 | 0.2 | 0 | 0 | 1 | 0.2 |
| Gamma | 0 | 0.0 | 0 | 0 | 0 | 0.0 |
| Lognormal | 0 | 0.0 | 2 | 0 | 0 | 0.0 |
| Gaussian–gamma | 1 | 0.2 | 42 | 8 | 10 | 2.0 |
| Gaussian–lognormal | 2 | 0.4 | 19 | 4 | 1 | 0.2 |
| Gamma–Gaussian | 2 | 0.4 | 38 | 8 | 3 | 0.6 |
| Gamma–lognormal | 0 | 0.0 | 0 | 0 | 0 | 0.0 |
| Lognormal–Gaussian | 450 | 98.7 | 399 | 80 | 485 | 97.0 |
| Lognormal–gamma | 0 | 0.0 | 0 | 0 | 0 | 0.0 |
| PPSM joint distributions | MSRC | BSDS | COCO | |||
|---|---|---|---|---|---|---|
| # of best segmented images | Best performance (%) | # of best segmented images | Best performance (%) | # of best segmented images | Best performance (%) | |
| Gaussian | 1 | 0.2 | 0 | 0 | 1 | 0.2 |
| Gamma | 0 | 0.0 | 0 | 0 | 0 | 0.0 |
| Lognormal | 0 | 0.0 | 2 | 0 | 0 | 0.0 |
| Gaussian–gamma | 1 | 0.2 | 42 | 8 | 10 | 2.0 |
| Gaussian–lognormal | 2 | 0.4 | 19 | 4 | 1 | 0.2 |
| Gamma–Gaussian | 2 | 0.4 | 38 | 8 | 3 | 0.6 |
| Gamma–lognormal | 0 | 0.0 | 0 | 0 | 0 | 0.0 |
| Lognormal–Gaussian | 450 | 98.7 | 399 | 80 | 485 | 97.0 |
| Lognormal–gamma | 0 | 0.0 | 0 | 0 | 0 | 0.0 |
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