Research map / Graph learning / Graph algorithms and clustering
Path Following with Adaptive Path Estimation for Graph Matching
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add adaptive path estimation (EST) to GNCCP | GNCCP · CMU house | computational time: about 4% of original time | Helped |
| Add adaptive path estimation (EST) to FGM | FGM · CMU house | computational time: about 18% of original time | Helped |
| Add EST to GNCCP | GNCCP · Pascal | computational time: about 2% of original time | Helped |
| Add EST to FGM | FGM · Pascal | computational time: about 15% of original time | Helped |
| Add EST to GNCCP | GNCCP · Caltech | computational time: 6.79 -> 0.27 | Helped |
| Add EST to GNCCP | GNCCP · Caltech | matching accuracy: 74.92 -> 75.60 | Helped |
| Add EST to GNCCP | GNCCP · CMU house example | true matches: 3/20 -> 16/20 | Helped |
| Add EST to GNCCP | GNCCP · Pascal example | true matches: 27/46 -> 38/46 | Helped |
| Add EST to FGM | FGM · CMU house example | true matches: 15/20 -> 17/20 | Helped |
| Add EST to FGM | FGM · Pascal example | true matches: 31/46 -> 39/46 | Helped |
| Add EST to FGM | FGM · Pascal | matching accuracy | No clear effect |
| Add EST to GNCCP | GNCCP · Caltech example | true matches: 12/17 -> 16/17 | Helped |
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