premise string | hypothesis string | label int64 |
|---|---|---|
| Algorithm | PercentageAccuracy | | |
| --- | --- | --- | --- |
| Complete | Viral-Pairs | Random-Pairs | |
| AlexNetRegression<br>VGGNet-16Regression | 53.01<br>56.12 | 57.72<br>60.11 | 54.19<br>58.23 | | | AlexNetSiamese<br>VGGNet-16Siamese | 58.17<br>60.23 | 61.11<br>66.15 | 59.87<br>63.15 |
| --- | --- | --- | --- |
| ViralNet | 65.87 | 76.20 | 74.38 | | 1 |
| Algorithm | PercentageAccuracy | | |
| --- | --- | --- | --- |
| Complete | Viral-Pairs | Random-Pairs | |
| AlexNetRegression<br>VGGNet-16Regression | 53.01<br>56.12 | 57.72<br>60.11 | 54.19<br>58.23 | | | #Datasets | MemeTracker | SinaWeibo |
| --- | --- | --- |
| #Nodes | 1,000 | 1,000 |
| #Edges | 4,323 | 1,671 |
| #Cascades | 2,762 | 2,907 |
| Maximal#infectionsincascades | 240 | 163 |
| Average#infectionsincascades | 14.85 | 6.62 | | 0 |
| Algorithm | PercentageAccuracy | |
| --- | --- | --- |
| Complete | Viral-Pairs | Random-Pairs | | | AlexNetRegression<br>VGGNet-16Regression | 53.01<br>56.12 | 57.72<br>60.11 | 54.19<br>58.23 |
| --- | --- | --- | --- |
| AlexNetSiamese<br>VGGNet-16Siamese | 58.17<br>60.23 | 61.11<br>66.15 | 59.87<br>63.15 |
| ViralNet | 65.87 | 76.20 | 74.38 | | 1 |
| Algorithm | PercentageAccuracy | |
| --- | --- | --- |
| Complete | Viral-Pairs | Random-Pairs | | | #Cascades | 2,762 | 2,907 |
| --- | --- | --- |
| Maximal#infectionsincascades | 240 | 163 |
| Average#infectionsincascades | 14.85 | 6.62 | | 0 |
| | | | | | |
| --- | --- | --- | --- | --- | --- |
| frb30-15-1 | t<br>c<br>r<br>n | 22,3<br>16,5M<br>105626<br>3863 | 20,9<br>11,1M<br>70924<br>3858 | 29,3<br>16,4M<br>102724<br>4138 | 14,1<br>7,5M<br>46727<br>2499 |
| frb30-15-2 | t<br>c<br>r<br>n | 84,9<br>45,7M<br>311040<br>15457 | 29,7<br>21,8M<br>149119<br... | | frb35-17-1 | t<br>c<br>r<br>n | 125,8<br>93,9M<br>533694<br>18587 | 193,7<br>144M<br>836462<br>40698 | 118<br>89,7M<br>514258<br>19167 | 250,9<br>180,9M<br>1,03M<br>50611 |
| --- | --- | --- | --- | --- | --- |
| rand-2-30-15 | t<br>c<br>r<br>n | 1240<br>114,5M<br>922251<br>28725 | 74,4<br>53M<br>443792<br>19846 | 98... | 1 |
| | | | | | |
| --- | --- | --- | --- | --- | --- |
| frb30-15-1 | t<br>c<br>r<br>n | 22,3<br>16,5M<br>105626<br>3863 | 20,9<br>11,1M<br>70924<br>3858 | 29,3<br>16,4M<br>102724<br>4138 | 14,1<br>7,5M<br>46727<br>2499 |
| frb30-15-2 | t<br>c<br>r<br>n | 84,9<br>45,7M<br>311040<br>15457 | 29,7<br>21,8M<br>149119<br... | | | | ARCORIENTED | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| s11-f9 | t<br>c<br>r<br>n | 18,8<br>25,03M<br>1,1M<br>1202 | 12,8<br>19,3M<br>910060<br>1153 | 14,6<br>13,2M<br>529228<br>1155 | 14,8<br>20,8M<br>1,04M<br>1145 | 19<br>21M<br>1,01M<br>1148 | 14,2<br>16,8M<... | 0 |
| | | | | | |
| --- | --- | --- | --- | --- | --- |
| frb30-15-1 | t<br>c<br>r<br>n | 22,3<br>16,5M<br>105626<br>3863 | 20,9<br>11,1M<br>70924<br>3858 | 29,3<br>16,4M<br>102724<br>4138 | 14,1<br>7,5M<br>46727<br>2499 | | | frb30-15-2 | t<br>c<br>r<br>n | 84,9<br>45,7M<br>311040<br>15457 | 29,7<br>21,8M<br>149119<br>7935 | 118,9<br>90M<br>624360<br>25148 | 95<br>68,9M<br>472124<br>24467 |
| --- | --- | --- | --- | --- | --- |
| frb35-17-1 | t<br>c<br>r<br>n | 125,8<br>93,9M<br>533694<br>18587 | 193,7<br>144M<br>836462<br>40698 | 118<br>... | 1 |
| | | | | | |
| --- | --- | --- | --- | --- | --- |
| frb30-15-1 | t<br>c<br>r<br>n | 22,3<br>16,5M<br>105626<br>3863 | 20,9<br>11,1M<br>70924<br>3858 | 29,3<br>16,4M<br>102724<br>4138 | 14,1<br>7,5M<br>46727<br>2499 | | | s11-f9 | t<br>c<br>r<br>n | 18,8<br>25,03M<br>1,1M<br>1202 | 12,8<br>19,3M<br>910060<br>1153 | 14,6<br>13,2M<br>529228<br>1155 | 14,8<br>20,8M<br>1,04M<br>1145 | 19<br>21M<br>1,01M<br>1148 | 14,2<br>16,8M<br>737803<br>1159 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| s11-f8 | t<br>c<br>r<br>n | 37,5<br>46,5M... | 0 |
| | BL | SL | SR | BH | SH | Ins |
| --- | --- | --- | --- | --- | --- | --- |
| BL | 15 | 4 | - | 6 | 1 | 1 |
| SL | 2 | 17 | 1 | - | 9 | 15 | | | SR | 2 | 1 | 27 | 1 | 5 | 8 |
| --- | --- | --- | --- | --- | --- | --- |
| BH | 5 | - | - | 14 | 2 | 6 |
| SH | - | 7 | 4 | - | 9 | 12 |
| Del | 1 | 2 | - | - | - | - |
| Total | 25 | 31 | 32 | 21 | 26 | 42 | | 1 |
| | BL | SL | SR | BH | SH | Ins |
| --- | --- | --- | --- | --- | --- | --- |
| BL | 15 | 4 | - | 6 | 1 | 1 |
| SL | 2 | 17 | 1 | - | 9 | 15 | | | | BL | SL | SR | BH | SH | Ins |
| --- | --- | --- | --- | --- | --- | --- |
| BL | 19 | 3 | 1 | - | - | 9 |
| SL | 3 | 25 | - | - | - | 12 |
| SR | 1 | 2 | 31 | - | 1 | 26 |
| BH | 1 | - | - | 20 | 2 | 15 |
| SH | - | - | - | 1 | 23 | 28 |
| Del | 1 | 1 | - | - | - | - |
| Total | 25 | 31 | 32 | 21 | 26 | 90 | | 0 |
| | BL | SL | SR | BH | SH | Ins |
| --- | --- | --- | --- | --- | --- | --- |
| BL | 15 | 4 | - | 6 | 1 | 1 |
| SL | 2 | 17 | 1 | - | 9 | 15 | | | SR | 2 | 1 | 27 | 1 | 5 | 8 |
| --- | --- | --- | --- | --- | --- | --- |
| BH | 5 | - | - | 14 | 2 | 6 |
| SH | - | 7 | 4 | - | 9 | 12 |
| Del | 1 | 2 | - | - | - | - |
| Total | 25 | 31 | 32 | 21 | 26 | 42 | | 1 |
| | BL | SL | SR | BH | SH | Ins |
| --- | --- | --- | --- | --- | --- | --- |
| BL | 15 | 4 | - | 6 | 1 | 1 |
| SL | 2 | 17 | 1 | - | 9 | 15 | | | SH | - | - | - | 1 | 23 | 28 |
| --- | --- | --- | --- | --- | --- | --- |
| Del | 1 | 1 | - | - | - | - |
| Total | 25 | 31 | 32 | 21 | 26 | 90 | | 0 |
| | auto-exposure | activecontrol | | |
| --- | --- | --- | --- | --- |
| σ=0.5 | σ=1 | σ=2 | | |
| DPM | 0.48 | 0.51 | 0.57 | 0.60 | | | BoW | 0.38 | 0.49 | 0.51 | 0.49 |
| --- | --- | --- | --- | --- |
| R-CNN | 0.61 | 0.56 | 0.60 | 0.60 |
| SPP-net | 0.63 | 0.66 | 0.69 | 0.66 | | 1 |
| | auto-exposure | activecontrol | | |
| --- | --- | --- | --- | --- |
| σ=0.5 | σ=1 | σ=2 | | |
| DPM | 0.48 | 0.51 | 0.57 | 0.60 | | | TrainingData | TestData | |
| --- | --- | --- |
| ILSVRC2012Val | WebVisionVal | |
| 1K<br>D<br>ImageNet | 56.15 | 52.58 |
| WebVision | 47.55 | 57.03 |
| E<br>VT | 51.99 | 53.94 |
| 1K<br>*D<br>ImageNet | 60.36 | 54.99 |
| E* | 56.58 | 57.98 | | 0 |
| | auto-exposure | activecontrol | | |
| --- | --- | --- | --- | --- |
| σ=0.5 | σ=1 | σ=2 | | |
| DPM | 0.48 | 0.51 | 0.57 | 0.60 | | | BoW | 0.38 | 0.49 | 0.51 | 0.49 |
| --- | --- | --- | --- | --- |
| R-CNN | 0.61 | 0.56 | 0.60 | 0.60 |
| SPP-net | 0.63 | 0.66 | 0.69 | 0.66 | | 1 |
| | auto-exposure | activecontrol | | |
| --- | --- | --- | --- | --- |
| σ=0.5 | σ=1 | σ=2 | | |
| DPM | 0.48 | 0.51 | 0.57 | 0.60 | | | 1K<br>D<br>ImageNet | 56.15 | 52.58 |
| --- | --- | --- |
| WebVision | 47.55 | 57.03 |
| E<br>VT | 51.99 | 53.94 |
| 1K<br>*D<br>ImageNet | 60.36 | 54.99 |
| E* | 56.58 | 57.98 | | 0 |
| ac | 200 | 150 | 130 | 110 | 90 | 70 | 50 | 30 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 0.54 | 3.2 | 8.7 | 22 | 87 | 430 | - | - |
| DL | 0.004 | 0.042 | 0.28 | 0.98 | 4.8 | 31 | 270 | - |
| BMR | 0.008 | 0.041 | 0.074 | 0.17 | 2.3 | 5.7 | 21 | 140 |
| HBC | 0.004 | 0.018 | 0.064 | 0.16 | 0.... | | cDFS | 0.001 | 0.005 | 0.019 | 0.051 | 0.18 | 0.95 | 8.4 | 170 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| \|F\| | 81 | 447 | 990 | 2000 | 4322 | 10968 | 32207 | 135439 |
| \|F\| | 57.48 | 56.34 | 72.85 | 72.23 | 326.66 | 326.08 | 325.31 | 430.39 |
| \|dual(F)\| | 253 | 1039 | 1916 | 3547 | 7617 | 174... | 1 |
| ac | 200 | 150 | 130 | 110 | 90 | 70 | 50 | 30 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 0.54 | 3.2 | 8.7 | 22 | 87 | 430 | - | - |
| DL | 0.004 | 0.042 | 0.28 | 0.98 | 4.8 | 31 | 270 | - |
| BMR | 0.008 | 0.041 | 0.074 | 0.17 | 2.3 | 5.7 | 21 | 140 |
| HBC | 0.004 | 0.018 | 0.064 | 0.16 | 0.... | | l | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 4.7 | 51 | 110 | 340 | - | - | - | - |
| DL | 0.11 | 6.4 | 44 | 210 | - | - | - | - |
| BMR | 0.047 | 2.2 | 5.1 | 16 | 130 | - | - | - |
| HBC | 110 | - | - | - | - | - | - | - |
| KS | 0.057 | 2.... | 0 |
| ac | 200 | 150 | 130 | 110 | 90 | 70 | 50 | 30 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 0.54 | 3.2 | 8.7 | 22 | 87 | 430 | - | - |
| DL | 0.004 | 0.042 | 0.28 | 0.98 | 4.8 | 31 | 270 | - |
| BMR | 0.008 | 0.041 | 0.074 | 0.17 | 2.3 | 5.7 | 21 | 140 |
| HBC | 0.004 | 0.018 | 0.064 | 0.16 | 0.... | | \|F\| | 57.48 | 56.34 | 72.85 | 72.23 | 326.66 | 326.08 | 325.31 | 430.39 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| \|dual(F)\| | 253 | 1039 | 1916 | 3547 | 7617 | 17486 | 47137 | 185218 |
| \|S\| | 2.57 | 3.77 | 4.25 | 4.73 | 5.09 | 5.70 | 6.46 | 7.32 | | 1 |
| ac | 200 | 150 | 130 | 110 | 90 | 70 | 50 | 30 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 0.54 | 3.2 | 8.7 | 22 | 87 | 430 | - | - |
| DL | 0.004 | 0.042 | 0.28 | 0.98 | 4.8 | 31 | 270 | - |
| BMR | 0.008 | 0.041 | 0.074 | 0.17 | 2.3 | 5.7 | 21 | 140 |
| HBC | 0.004 | 0.018 | 0.064 | 0.16 | 0.... | | KS | 0.057 | 2.6 | 4.6 | 20 | 97 | - | - | - |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| RS | 0.009 | 0.052 | 0.14 | 0.41 | 1.6 | 15 | 98 | 420 |
| DFS | 0.006 | 0.044 | 0.09 | 0.28 | 0.94 | 12 | 40 | 180 |
| \|F\| | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| \|F\| | 8 | 8 | 8 | 8 | 8 | 8 ... | 0 |
| Dataset | PSNR | SSIM |
| --- | --- | --- |
| ShanghaiTechPartA | 23.79 | 0.76 |
| ShanghaiTechPartB | 27.02 | 0.89 | | | UCFCC50 | 18.76 | 0.52 |
| --- | --- | --- |
| TheWorldExpo’10 | 26.94 | 0.92 |
| TheUCSD | 20.02 | 0.86 |
| TRANCOS | 27.10 | 0.93 | | 1 |
| Dataset | PSNR | SSIM |
| --- | --- | --- |
| ShanghaiTechPartA | 23.79 | 0.76 |
| ShanghaiTechPartB | 27.02 | 0.89 | | | Metric(avg.) | NAMIC | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | | |
| | | | | | | | | |
| PSNR(dB) | 24.36 | 26.51 | 27.14 | 27.30 | 27.26 | 27.81 | 29.04 | 30.35 |
| SSIM | 0.8771 | 0.8874 | 0.8934 | 0.8983 | 0.9166 | 0.9130 | 0.9173 | 0.9270 | | 0 |
| Dataset | PSNR | SSIM |
| --- | --- | --- |
| ShanghaiTechPartA | 23.79 | 0.76 |
| ShanghaiTechPartB | 27.02 | 0.89 |
| UCFCC50 | 18.76 | 0.52 | | | TheWorldExpo’10 | 26.94 | 0.92 |
| --- | --- | --- |
| TheUCSD | 20.02 | 0.86 |
| TRANCOS | 27.10 | 0.93 | | 1 |
| Dataset | PSNR | SSIM |
| --- | --- | --- |
| ShanghaiTechPartA | 23.79 | 0.76 |
| ShanghaiTechPartB | 27.02 | 0.89 |
| UCFCC50 | 18.76 | 0.52 | | | PSNR(dB) | 24.36 | 26.51 | 27.14 | 27.30 | 27.26 | 27.81 | 29.04 | 30.35 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| SSIM | 0.8771 | 0.8874 | 0.8934 | 0.8983 | 0.9166 | 0.9130 | 0.9173 | 0.9270 | | 0 |
| Group | Name | Nqorig | Nq |
| --- | --- | --- | --- |
| 4 | family(genderinflections) | 506 | 305 | | | 5 | gram1-adjective-to-adverb | 992 | 755 |
| --- | --- | --- | --- |
| 6 | gram2-opposite | 812 | 305 |
| 7 | gram3-comparative | 1332 | 1259 |
| 8 | gram4-superlative | 1122 | 505 |
| 9 | gram5-present-participle | 1056 | 991 |
| 11 | gram7-past-tense | 1560 | 1331 |
| 12 | gram8-plural(nouns) | 1332 | 991 |
| 13 |... | 1 |
| Group | Name | Nqorig | Nq |
| --- | --- | --- | --- |
| 4 | family(genderinflections) | 506 | 305 | | | SemanticArchitecture | CBOW | CLOW | DIEM |
| --- | --- | --- | --- |
| SemanticVectorDim. | 500500 | 500 | |
| SEMANTICTOTAL | 81.0280.19 | 80.19 | |
| adjective-to-adverb<br>opposite<br>comparative<br>superlative<br>present-participle<br>nationality-adjective<br>past-tense<br>plural<br>plural-verbs | 37.7035.08<b... | 0 |
| Group | Name | Nqorig | Nq |
| --- | --- | --- | --- |
| 4 | family(genderinflections) | 506 | 305 |
| 5 | gram1-adjective-to-adverb | 992 | 755 |
| 6 | gram2-opposite | 812 | 305 | | | 7 | gram3-comparative | 1332 | 1259 |
| --- | --- | --- | --- |
| 8 | gram4-superlative | 1122 | 505 |
| 9 | gram5-present-participle | 1056 | 991 |
| 11 | gram7-past-tense | 1560 | 1331 |
| 12 | gram8-plural(nouns) | 1332 | 991 |
| 13 | gram9-plural-verbs | 870 | 649 | | 1 |
| Group | Name | Nqorig | Nq |
| --- | --- | --- | --- |
| 4 | family(genderinflections) | 506 | 305 |
| 5 | gram1-adjective-to-adverb | 992 | 755 |
| 6 | gram2-opposite | 812 | 305 | | | SEMANTICTOTAL | 81.0280.19 | 80.19 |
| --- | --- | --- |
| adjective-to-adverb<br>opposite<br>comparative<br>superlative<br>present-participle<br>nationality-adjective<br>past-tense<br>plural<br>plural-verbs | 37.7035.08<br>36.2140.15<br>86.7187.31<br>80.1282.00<br>77.2780.78<br>90.4390.18<br>72.3773.40<br>80.1881.83... | 0 |
| n | Definitional | Pruning | #Pretropisms | MixedVolume |
| --- | --- | --- | --- | --- |
| 3 | 0.008 | 0.20 | 7 | 319 | | | 4 | 0.11 | 0.42 | 18 | 7,384 |
| --- | --- | --- | --- | --- |
| 5 | 1.33 | 0.76 | 58 | 152,054 |
| 6 | 13.03 | 2.75 | 171 | 4,305,758 |
| 7 | 243.88 | 20.17 | 614 | 91,381,325 |
| 8 | 2054.11 | 220.14 | 1,878 | 2,097,221,068 | | 1 |
| n | Definitional | Pruning | #Pretropisms | MixedVolume |
| --- | --- | --- | --- | --- |
| 3 | 0.008 | 0.20 | 7 | 319 | | | n | Definitional | Pruning | #Pretropisms | MixedVolume |
| --- | --- | --- | --- | --- |
| 4 | 0.02 | 0.62 | 2 | 4 |
| 5 | 0.43 | 1.04 | 0 | 14 |
| 6 | 17.90 | 1.56 | 8 | 26 |
| 7 | 301.26 | 2.57 | 28 | 132 |
| 8 | 33681.66 | 9.43 | 94 | 320 |
| 9 | | 44.97 | 259 | 1224 |
| 10 | | 978.67 | 712 | 3594 | | 0 |
| n | Definitional | Pruning | #Pretropisms | MixedVolume |
| --- | --- | --- | --- | --- |
| 3 | 0.008 | 0.20 | 7 | 319 |
| 4 | 0.11 | 0.42 | 18 | 7,384 |
| 5 | 1.33 | 0.76 | 58 | 152,054 |
| 6 | 13.03 | 2.75 | 171 | 4,305,758 | | | 7 | 243.88 | 20.17 | 614 | 91,381,325 |
| --- | --- | --- | --- | --- |
| 8 | 2054.11 | 220.14 | 1,878 | 2,097,221,068 | | 1 |
| n | Definitional | Pruning | #Pretropisms | MixedVolume |
| --- | --- | --- | --- | --- |
| 3 | 0.008 | 0.20 | 7 | 319 |
| 4 | 0.11 | 0.42 | 18 | 7,384 |
| 5 | 1.33 | 0.76 | 58 | 152,054 |
| 6 | 13.03 | 2.75 | 171 | 4,305,758 | | | 8 | 33681.66 | 9.43 | 94 | 320 |
| --- | --- | --- | --- | --- |
| 9 | | 44.97 | 259 | 1224 |
| 10 | | 978.67 | 712 | 3594 | | 0 |
| Mesh<br>size<br>h | sHHO(1) | uHHO(1) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Displacement | Gradient | Displacement | Gradient | | | | | |
| Error | Order | Error | Order | Error | Order | Error | Order | |
| 1.15e-1 | 5.98e-2 | - | 3.22e-1 | - | 4.00e-2 | - | 1.23e-1 | - ... | | 3.45e-2 | 6.30e-3 | 2.05 | 3.15e-2 | 1.86 | 3.80e-3 | 2.42 | 6.60e-2 | 0.83 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2.52e-2 | 3.42e-3 | 1.95 | 1.83e-2 | 1.73 | 2.03e-3 | 2.05 | 5.11e-2 | 0.94 |
| 1.64e-2 | 1.49e-3 | 1.93 | 7.98e-3 | 1.93 | 9.76e-4 | 1.72 | 3.09e-2 | 1.08 | | 1 |
| Mesh<br>size<br>h | sHHO(1) | uHHO(1) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Displacement | Gradient | Displacement | Gradient | | | | | |
| Error | Order | Error | Order | Error | Order | Error | Order | |
| 1.15e-1 | 5.98e-2 | - | 3.22e-1 | - | 4.00e-2 | - | 1.23e-1 | - ... | | Method | 1500 | 5000 | 20000 | 80000 |
| --- | --- | --- | --- | --- |
| DC | (0.0553,0.2692) | (0.0286,0.1292) | (0.0144,0.0738) | (0.0072,0.0401) |
| HF | (0.0881,0.9840) | (0.0473,0.5649) | (0.0210,0.5558) | (0.0093,0.5570) |
| BD | (0.1333,1.307) | (0.0781,1.285) | (0.0445,1.482) | (0.0277,1.324) |
| (d,d)2∞ | |... | 0 |
| Mesh<br>size<br>h | sHHO(1) | uHHO(1) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Displacement | Gradient | Displacement | Gradient | | | | | |
| Error | Order | Error | Order | Error | Order | Error | Order | |
| 1.15e-1 | 5.98e-2 | - | 3.22e-1 | - | 4.00e-2 | - | 1.23e-1 | - ... | | 2.52e-2 | 3.42e-3 | 1.95 | 1.83e-2 | 1.73 | 2.03e-3 | 2.05 | 5.11e-2 | 0.94 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1.64e-2 | 1.49e-3 | 1.93 | 7.98e-3 | 1.93 | 9.76e-4 | 1.72 | 3.09e-2 | 1.08 | | 1 |
| Mesh<br>size<br>h | sHHO(1) | uHHO(1) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Displacement | Gradient | Displacement | Gradient | | | | | |
| Error | Order | Error | Order | Error | Order | Error | Order | |
| 1.15e-1 | 5.98e-2 | - | 3.22e-1 | - | 4.00e-2 | - | 1.23e-1 | - ... | | HF | 0.987 | 3.14 | 12.0 | 47.3 |
| --- | --- | --- | --- | --- |
| BD | 74.2 | 227 | 940 | 4204 |
| timing(sec) | | | | | | 0 |
| Year | Bottega<br>Veneta | Burberr<br>Prorsum | Dior<br>Homme | Emporio<br>Armani | Erme.<br>Zegna | Givench | Gucci | Hermes | John<br>Varva | Louis<br>Vuitt | Neil<br>Barret | Prad | Thom<br>Brow |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2008 | 78 | 80 | 51 | 187 | 0 ... | | 2014 | 88 | 85 | 82 | 192 | 79 | 100 | 75 | 81 | 71 | 83 | 76 | 73 | 82 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2015 | 82 | 85 | 80 | 150 | 80 | 104 | 72 | 72 | 75 | 76 | 76 | 65 | 81 | | 1 |
| Year | Bottega<br>Veneta | Burberr<br>Prorsum | Dior<br>Homme | Emporio<br>Armani | Erme.<br>Zegna | Givench | Gucci | Hermes | John<br>Varva | Louis<br>Vuitt | Neil<br>Barret | Prad | Thom<br>Brow |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2008 | 78 | 80 | 51 | 187 | 0 ... | | Name | Reviews | 5Star | 4Star | 3Star | 2Star | 1Star |
| --- | --- | --- | --- | --- | --- | --- |
| FoodInc. | 2462 | 1949 | 357 | 78 | 30 | 48 |
| Boyhood | 2253 | 872 | 342 | 318 | 296 | 425 |
| FedUp | 1401 | 1069 | 185 | 82 | 29 | 36 |
| Blackfish | 955 | 750 | 117 | 42 | 15 | 31 |
| TheImitationGame | 829 | 57... | 0 |
| Year | Bottega<br>Veneta | Burberr<br>Prorsum | Dior<br>Homme | Emporio<br>Armani | Erme.<br>Zegna | Givench | Gucci | Hermes | John<br>Varva | Louis<br>Vuitt | Neil<br>Barret | Prad | Thom<br>Brow |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2008 | 78 | 80 | 51 | 187 | 0 ... | | 2013 | 86 | 85 | 79 | 135 | 73 | 57 | 79 | 66 | 65 | 79 | 68 | 76 | 79 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2014 | 88 | 85 | 82 | 192 | 79 | 100 | 75 | 81 | 71 | 83 | 76 | 73 | 82 |
| 2015 | 82 | 85 | 80 | 150 | 80 | 104 | 72 | 72 | 75 | 76 | 76 | 65 | 81 | | 1 |
| Year | Bottega<br>Veneta | Burberr<br>Prorsum | Dior<br>Homme | Emporio<br>Armani | Erme.<br>Zegna | Givench | Gucci | Hermes | John<br>Varva | Louis<br>Vuitt | Neil<br>Barret | Prad | Thom<br>Brow |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2008 | 78 | 80 | 51 | 187 | 0 ... | | Blackfish | 955 | 750 | 117 | 42 | 15 | 31 |
| --- | --- | --- | --- | --- | --- | --- |
| TheImitationGame | 829 | 577 | 158 | 54 | 14 | 26 |
| Super-SizeMe | 670 | 324 | 152 | 71 | 41 | 82 |
| InsideJob | 437 | 308 | 54 | 21 | 10 | 44 |
| Citizenfour | 199 | 168 | 17 | 10 | 1 | 3 | | 0 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 | | | B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>64.0 |
| --- | --- |
| B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| Two-stageHierarchicalModel | 81.5 | | 1 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 | | | Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 |
| B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>62.2 |
| B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
... | 0 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 |
| B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>64.0 | | | B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| --- | --- |
| Two-stageHierarchicalModel | 81.5 | | 1 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 |
| B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>64.0 | | | B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| --- | --- |
| Two-stageHierarchicalModel | 81.5 | | 0 |
| Roads | Sections | Length | PointsNumber | STime | MTime | RTime |
| --- | --- | --- | --- | --- | --- | --- |
| ZCABR | sec1 | 770.06m | 131681009 | 101.562s | 1331.77s | 23.4443s |
| LHSR | sec1 | 734.051m | 91212406 | 34.9641s | 462.631s | 11.0206s |
| sec2 | 593.169m | 69915170 | 24.2266s | 178.086s | 3.50449s | ... | | WPR | sec1 | 453.526m | 44234114 | 15.2498s | 0.131961s | 0.00027s |
| --- | --- | --- | --- | --- | --- | --- |
| sec2 | 632.114m | 51933545 | 19.9543s | 54.6281s | 6.75658s | |
| sec3 | 870.5m | 34694921 | 28.8413s | 58.7381s | 5.59397s | | | 1 |
| Roads | Sections | Length | PointsNumber | STime | MTime | RTime |
| --- | --- | --- | --- | --- | --- | --- |
| ZCABR | sec1 | 770.06m | 131681009 | 101.562s | 1331.77s | 23.4443s |
| LHSR | sec1 | 734.051m | 91212406 | 34.9641s | 462.631s | 11.0206s |
| sec2 | 593.169m | 69915170 | 24.2266s | 178.086s | 3.50449s | ... | | | Dist | StaffCost | TravelCost | CO2 | CarUse |
| --- | --- | --- | --- | --- | --- |
| Lon-1 | 204.64:206.93 | 841:974.67 | 82.54:85.79 | 133.83:163.75 | 0:0.25 |
| Lon-2 | 223.3:231.02 | 870.67:1014.67 | 89.71:103.04 | 148.94:192.85 | 0.06:0.33 |
| Lon-4 | 225.37:244.09 | 904.33:1276 | 94.63:116.74 | 158.77:194.59... | 0 |
| Roads | Sections | Length | PointsNumber | STime | MTime | RTime |
| --- | --- | --- | --- | --- | --- | --- |
| ZCABR | sec1 | 770.06m | 131681009 | 101.562s | 1331.77s | 23.4443s |
| LHSR | sec1 | 734.051m | 91212406 | 34.9641s | 462.631s | 11.0206s |
| sec2 | 593.169m | 69915170 | 24.2266s | 178.086s | 3.50449s | ... | | sec2 | 632.114m | 51933545 | 19.9543s | 54.6281s | 6.75658s |
| --- | --- | --- | --- | --- | --- |
| sec3 | 870.5m | 34694921 | 28.8413s | 58.7381s | 5.59397s | | 1 |
| Roads | Sections | Length | PointsNumber | STime | MTime | RTime |
| --- | --- | --- | --- | --- | --- | --- |
| ZCABR | sec1 | 770.06m | 131681009 | 101.562s | 1331.77s | 23.4443s |
| LHSR | sec1 | 734.051m | 91212406 | 34.9641s | 462.631s | 11.0206s |
| sec2 | 593.169m | 69915170 | 24.2266s | 178.086s | 3.50449s | ... | | Blon-4 | 708.25:722.53 | 2183.33:2545.67 | 267.85:272.34 | 584.19:637.26 | 0.08:0.33 |
| --- | --- | --- | --- | --- | --- |
| Blon-8 | 688.94:658.52 | 2209:2772 | 272.22:311.52 | 586.81:637.5 | 0.08:0.38 |
| Blon-rnd | 730.3:666.29 | 2256:2717.67 | 251.31:263.1 | 580.16:602.47 | 0.09:0.36 | | 0 |
| Approach | aero. | bicy. | boat | bott. | bus | car | chair | table | moto. | sofa | train |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Acc(Baseline)π/6 | 0.80 | 0.84 | 0.62 | 0.96 | 0.95 | 0.85 | 0.75 | 0.86 | 0.88 | 0.87 | 0.82 | | | Acc(Ours)π/6 | 0.84 | 0.84 | 0.58 | 0.96 | 0.92 | 0.88 | 0.91 | 0.57 | 0.88 | 0.87 | 0.85 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MedErr(Baseline) | 10.2 | 12.2 | 18.5 | 6.5 | 4.5 | 6.4 | 12.4 | 8.6 | 13.0 | 11.0 | 5.7 |
| MedErr(Ours) | 8.7 | 11.5 | 18.4 | 6.4 | 2.4 | 4.5 | 7.3 ... | 1 |
| Approach | aero. | bicy. | boat | bott. | bus | car | chair | table | moto. | sofa | train |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Acc(Baseline)π/6 | 0.80 | 0.84 | 0.62 | 0.96 | 0.95 | 0.85 | 0.75 | 0.86 | 0.88 | 0.87 | 0.82 | | | Methods | aeroplane | bicycle | boat | bottle | bus | car | chair | diningtable | motorbike | sofa | train | tvmonitor | Average |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ObjectDetection(AP) | | | | | | | | | | | | | |
| DPM | 42.2 | 49.6 | 6.0 | 20.0 | 54.... | 0 |
| Approach | aero. | bicy. | boat | bott. | bus | car | chair | table | moto. | sofa | train |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Acc(Baseline)π/6 | 0.80 | 0.84 | 0.62 | 0.96 | 0.95 | 0.85 | 0.75 | 0.86 | 0.88 | 0.87 | 0.82 | | | Acc(Ours)π/6 | 0.84 | 0.84 | 0.58 | 0.96 | 0.92 | 0.88 | 0.91 | 0.57 | 0.88 | 0.87 | 0.85 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MedErr(Baseline) | 10.2 | 12.2 | 18.5 | 6.5 | 4.5 | 6.4 | 12.4 | 8.6 | 13.0 | 11.0 | 5.7 |
| MedErr(Ours) | 8.7 | 11.5 | 18.4 | 6.4 | 2.4 | 4.5 | 7.3 ... | 1 |
| Approach | aero. | bicy. | boat | bott. | bus | car | chair | table | moto. | sofa | train |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Acc(Baseline)π/6 | 0.80 | 0.84 | 0.62 | 0.96 | 0.95 | 0.85 | 0.75 | 0.86 | 0.88 | 0.87 | 0.82 | | | DPM-VOC+VP | 17.0 | 24.7 | 1.0 | – | 49.0 | 30.1 | 6.6 | 3.0 | 17.2 | 7.7 | 20.4 | 20.2 | 17.9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Oursw/oExtra | 23.3 | 19.2 | 8.4 | – | 52.6 | 27.0 | 9.9 | 5.1 | 23.6 | 20.9 | 27.4 | 27.9 | 22.3 |
| OursFull | 28.0 | 23.7 | 10.7 |... | 0 |
| Key | Explanation |
| --- | --- |
| d: | [TheEntireDictionary] | | | la: | [IP:PortinNetwork-ByteOrder] |
| --- | --- |
| m: | [MessageTypeHeader,e.g.,getpeers] |
| peer: | [LocalPeerID] |
| share: | [LocalShareID] |
| e: | [End] | | 1 |
| Key | Explanation |
| --- | --- |
| d: | [TheEntireDictionary] | | | Usecase | Typeofdata | Securityneed | Specificity |
| --- | --- | --- | --- |
| PeerSense | BDADDR:social-ID | private | device-specific |
| SCAMPI | SCAMPI-ID:social-ID | private | device-specific |
| FoFfinder | bearertoken | private | user-specific |
| Publickeydistribution | publickey | public | user-specific | | 0 |
| Key | Explanation |
| --- | --- |
| d: | [TheEntireDictionary] |
| la: | [IP:PortinNetwork-ByteOrder] |
| m: | [MessageTypeHeader,e.g.,getpeers] |
| peer: | [LocalPeerID] | | | share: | [LocalShareID] |
| --- | --- |
| e: | [End] | | 1 |
| Key | Explanation |
| --- | --- |
| d: | [TheEntireDictionary] |
| la: | [IP:PortinNetwork-ByteOrder] |
| m: | [MessageTypeHeader,e.g.,getpeers] |
| peer: | [LocalPeerID] | | | FoFfinder | bearertoken | private | user-specific |
| --- | --- | --- | --- |
| Publickeydistribution | publickey | public | user-specific | | 0 |
| c1 | c2 | c3 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | c12 | c13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.8833 | 0.8860 | 0.8461 | 0.8531 | 0.8383 | 0.8258 | 0.8608 | 0.8586 | 0.8229 | 0.8197 | 0.8829 | 0.8461 | 0.8852 | | | 0.8246 | 0.8390 | 0.8837 | 0.8920 | 0.8313 | 0.8270 | 0.8208 | 0.8749 | 0.8624 | 0.8678 | 0.8957 | 0.8115 | 0.8815 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.8644 | 0.8619 | 0.8502 | 0.8882 | 0.9262 | 0.9472 | 0.9378 | 0.8953 | 0.8998 | 0.9252 | 0.8556 | 0.9341 | 0.9336 |
| ... | 1 |
| c1 | c2 | c3 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | c12 | c13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.8833 | 0.8860 | 0.8461 | 0.8531 | 0.8383 | 0.8258 | 0.8608 | 0.8586 | 0.8229 | 0.8197 | 0.8829 | 0.8461 | 0.8852 | | | c1 | c2 | c3 | c4 | c5 | AA | OA |
| --- | --- | --- | --- | --- | --- | --- |
| 0.8826 | 0.8682 | 0.8553 | 0.8992 | 0.8697 | 0.8750 | 0.8864 |
| 0.8474 | 0.8974 | 0.8794 | 0.8279 | 0.9098 | 0.8724 | 0.8835 |
| 0.9132 | 0.9209 | 0.9174 | 0.8656 | 0.9408 | 0.9116 | 0.9187 |
| 0.9126 | 0.9400 | 0.9089 | 0.9337 | 0.9159... | 0 |
| c1 | c2 | c3 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | c12 | c13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.8833 | 0.8860 | 0.8461 | 0.8531 | 0.8383 | 0.8258 | 0.8608 | 0.8586 | 0.8229 | 0.8197 | 0.8829 | 0.8461 | 0.8852 |
| 0.8246 | 0.8390 | 0.8837 | 0.8920 | 0.8313 | 0.8... | | 0.8900 | 0.8707 | 0.8833 | 0.8939 | 0.9321 | 0.9587 | 0.8936 | 0.9594 | 0.9283 | 0.9264 | 0.9241 | 0.8704 | 0.9223 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.9792 | 0.9378 | 0.9278 | 0.9584 | 0.9625 | 0.9241 | 0.9771 | 0.9860 | 0.9025 | 0.9010 | 0.9819 | 0.9327 | 0.9376 |
| ... | 1 |
| c1 | c2 | c3 | c4 | c5 | c6 | c7 | c8 | c9 | c10 | c11 | c12 | c13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.8833 | 0.8860 | 0.8461 | 0.8531 | 0.8383 | 0.8258 | 0.8608 | 0.8586 | 0.8229 | 0.8197 | 0.8829 | 0.8461 | 0.8852 |
| 0.8246 | 0.8390 | 0.8837 | 0.8920 | 0.8313 | 0.8... | | 0.9645 | 0.9439 | 0.9120 | 0.9428 | 0.9409 | 0.9408 | 0.9522 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.9354 | 0.9423 | 0.9719 | 0.9759 | 0.9645 | 0.9580 | 0.9770 | | 0 |
| Newspaper | Facebookprofile | Posts | Comments |
| --- | --- | --- | --- |
| TheWallStreetJournal | wsj | 1577 | 136969 |
| TheNewYorkTimes | nytimes | 265 | 98099 |
| USAToday | usatoday | 560 | 155893 |
| LosAngelesTimes | latimes | 532 | 124477 |
| SanJoseMercuryNews | mercurynews | 0 | 0 |
| NewYorkDailyNews | NYD... | | TampaBayTimes | tampabaycom | 1539 | 76388 |
| --- | --- | --- | --- |
| ThePlainDealer | ThePlainDealerCLE | 4 | 33 |
| ThePhiladelphiaInquirer | phillyinquirer | 2124 | 10491 |
| StarTribune | startribune | 2820 | 106357 |
| TheArizonaRepublic | azcentral | 2073 | 151590 |
| HonoluluStar-Advertiser | staradvertiser... | 1 |
| Newspaper | Facebookprofile | Posts | Comments |
| --- | --- | --- | --- |
| TheWallStreetJournal | wsj | 1577 | 136969 |
| TheNewYorkTimes | nytimes | 265 | 98099 |
| USAToday | usatoday | 560 | 155893 |
| LosAngelesTimes | latimes | 532 | 124477 |
| SanJoseMercuryNews | mercurynews | 0 | 0 |
| NewYorkDailyNews | NYD... | | Outlet | N | Outlet | N |
| --- | --- | --- | --- |
| HeavilyRightLeaning | HeavilyLeftLeaning | | |
| RealClearPolitics | 7 | HuffingtonPost | 68 |
| WashingtonTimes | 11 | Vox | 16 |
| Breitbart | 7 | Politico | 94 |
| TheHill | 32 | NewYorker | 13 |
| NationalReview | 10 | | |
| RightLeaning | LeftLeaning | | ... | 0 |
| Newspaper | Facebookprofile | Posts | Comments |
| --- | --- | --- | --- |
| TheWallStreetJournal | wsj | 1577 | 136969 |
| TheNewYorkTimes | nytimes | 265 | 98099 |
| USAToday | usatoday | 560 | 155893 |
| LosAngelesTimes | latimes | 532 | 124477 | | | SanJoseMercuryNews | mercurynews | 0 | 0 |
| --- | --- | --- | --- |
| NewYorkDailyNews | NYDailyNews | 1637 | 124948 |
| NewYorkPost | NYPost | 479 | 132715 |
| TheWashingtonPost | washingtonpost | 232 | 101260 |
| ChicagoSun-Times | thechicagosuntimes | 2215 | 64675 |
| TheDenverPost | denverpost | 1376 | 113621 |
... | 1 |
| Newspaper | Facebookprofile | Posts | Comments |
| --- | --- | --- | --- |
| TheWallStreetJournal | wsj | 1577 | 136969 |
| TheNewYorkTimes | nytimes | 265 | 98099 |
| USAToday | usatoday | 560 | 155893 |
| LosAngelesTimes | latimes | 532 | 124477 | | | OrangeCounty<br>Register | 12 | | |
| --- | --- | --- | --- |
| LasVegasReview-<br>Journal | 14 | | | | 0 |
| Knownbits | Meanvalueofninsimulations | ValueofnbyTheorem?? |
| --- | --- | --- |
| 30 | 7.0 | 7 |
| 28 | 7.4 | 8 |
| 26 | 8.0 | 8 |
| 24 | 8.5 | 9 |
| 22 | 9.0 | 10 |
| 20 | 9.8 | 11 |
| 18 | 11.0 | 12 |
| 16 | 12.5 | 14 |
| 14 | 14.3 | 17 |
| 12 | 17.1 | 21 | | | 10 | 20.7 | 30 |
| --- | --- | --- |
| 8 | 27.3 | 54 |
| 6 | 50 | - | | 1 |
| Knownbits | Meanvalueofninsimulations | ValueofnbyTheorem?? |
| --- | --- | --- |
| 30 | 7.0 | 7 |
| 28 | 7.4 | 8 |
| 26 | 8.0 | 8 |
| 24 | 8.5 | 9 |
| 22 | 9.0 | 10 |
| 20 | 9.8 | 11 |
| 18 | 11.0 | 12 |
| 16 | 12.5 | 14 |
| 14 | 14.3 | 17 |
| 12 | 17.1 | 21 | | | Axon | meanvalue[mA] | standarddeviation[mA] |
| --- | --- | --- |
| 1 | 0.14 | 0.01 |
| 2 | 0.56 | 0.06 |
| 3 | 1.44 | 0.15 |
| 4 | 2.97 | 0.31 |
| 5 | 5.30 | 0.56 |
| 6 | 8.65 | 0.91 |
| 7 | 13.20 | 1.39 |
| 8 | 19.15 | 2.02 |
| 9 | 26.67 | 2.81 |
| 10 | 36.06 | 3.80 | | 0 |
| Knownbits | Meanvalueofninsimulations | ValueofnbyTheorem?? |
| --- | --- | --- |
| 30 | 7.0 | 7 |
| 28 | 7.4 | 8 |
| 26 | 8.0 | 8 |
| 24 | 8.5 | 9 |
| 22 | 9.0 | 10 |
| 20 | 9.8 | 11 |
| 18 | 11.0 | 12 |
| 16 | 12.5 | 14 |
| 14 | 14.3 | 17 |
| 12 | 17.1 | 21 |
| 10 | 20.7 | 30 | | | 8 | 27.3 | 54 |
| --- | --- | --- |
| 6 | 50 | - | | 1 |
| Knownbits | Meanvalueofninsimulations | ValueofnbyTheorem?? |
| --- | --- | --- |
| 30 | 7.0 | 7 |
| 28 | 7.4 | 8 |
| 26 | 8.0 | 8 |
| 24 | 8.5 | 9 |
| 22 | 9.0 | 10 |
| 20 | 9.8 | 11 |
| 18 | 11.0 | 12 |
| 16 | 12.5 | 14 |
| 14 | 14.3 | 17 |
| 12 | 17.1 | 21 |
| 10 | 20.7 | 30 | | | 7 | 13.20 | 1.39 |
| --- | --- | --- |
| 8 | 19.15 | 2.02 |
| 9 | 26.67 | 2.81 |
| 10 | 36.06 | 3.80 | | 0 |
| TypeofHashFamily | PreviousResults | OurResults |
| --- | --- | --- |
| LinearProbing | | |
| 2-universalhashing<br>4-wiseindependence | 4logT<br>2.5logT | 3logT<br>2logT |
| BalancedAllocationswithdChoices | | |
| 2-universalhashing<br>4-wiseindependence | (d+2)logT<br>(d+1)logT | (d+1)logT<br>— | | | BloomFilters | | |
| --- | --- | --- |
| 2-universalhashing<br>4-wiseindependence | 4logT<br>3logT | 3logT<br>— | | 1 |
| TypeofHashFamily | PreviousResults | OurResults |
| --- | --- | --- |
| LinearProbing | | |
| 2-universalhashing<br>4-wiseindependence | 4logT<br>2.5logT | 3logT<br>2logT |
| BalancedAllocationswithdChoices | | |
| 2-universalhashing<br>4-wiseindependence | (d+2)logT<br>(d+1)logT | (d+1)logT<br>— | | | Method | 64bits96bits128bits256bits |
| --- | --- |
| SVHN | |
| DeepHash | 4.064.324.144.11 |
| DMIH | 10.4010.949.108.17 |
| NUS-WIDE | |
| DeepHash | 9.239.598.998.97 |
| DMIH | 9.729.849.519.39 | | 0 |
| TypeofHashFamily | PreviousResults | OurResults |
| --- | --- | --- |
| LinearProbing | | |
| 2-universalhashing<br>4-wiseindependence | 4logT<br>2.5logT | 3logT<br>2logT |
| BalancedAllocationswithdChoices | | |
| 2-universalhashing<br>4-wiseindependence | (d+2)logT<br>(d+1)logT | (d+1)logT<br>— | | | BloomFilters | | |
| --- | --- | --- |
| 2-universalhashing<br>4-wiseindependence | 4logT<br>3logT | 3logT<br>— | | 1 |
| TypeofHashFamily | PreviousResults | OurResults |
| --- | --- | --- |
| LinearProbing | | |
| 2-universalhashing<br>4-wiseindependence | 4logT<br>2.5logT | 3logT<br>2logT |
| BalancedAllocationswithdChoices | | |
| 2-universalhashing<br>4-wiseindependence | (d+2)logT<br>(d+1)logT | (d+1)logT<br>— | | | DeepHash | 4.064.324.144.11 |
| --- | --- |
| DMIH | 10.4010.949.108.17 |
| NUS-WIDE | |
| DeepHash | 9.239.598.998.97 |
| DMIH | 9.729.849.519.39 | | 0 |
| | CUHK01<br>VIPeRPRID<br>(N=871/485)t |
| --- | --- |
| SCSP<br>LSSCDL<br>TMA<br>(cid:96)1GL<br>SiameseLSTM | 53.5--<br>42.6--<br>43.8--<br>41.530.1-/50.1<br>42.4-- | | | MetricEnsemble<br>DNS | 45.9--<br>51.140.9-/69.0 |
| --- | --- |
| IDLA<br>DGD<br>MCP-CNN<br>GatedS-CNN<br>EDM<br>JointLearning<br>CAN | 34.8-65.0/47.5<br>38.664.0*-/66.6<br>47.822.0-/53.7<br>37.8--<br>40.9-86.6/-<br>35.8-72.5/-<br>--81.0/- |
| Ours | 56.343.693.2/77.0 | | 1 |
| | CUHK01<br>VIPeRPRID<br>(N=871/485)t |
| --- | --- |
| SCSP<br>LSSCDL<br>TMA<br>(cid:96)1GL<br>SiameseLSTM | 53.5--<br>42.6--<br>43.8--<br>41.530.1-/50.1<br>42.4-- | | | Cat | Method | Feature | Metric | | |
| --- | --- | --- | --- | --- | --- |
| | | | | | |
| A | XQDA<br>GOG<br>NFST<br>SCS | LOMO<br>GOG<br>LOMO,KCCA<br>CHS | -<br>-<br>-<br>- | XQDA<br>XQDA<br>NSFT<br>SCS | -<br>-<br>-<br>- |
| B | DCNN+<br>X-Corr<br>MTDnet | -<br>-<br>- | DCNN+<br>X-Corr<br>MTDnet | DVM<br>... | 0 |
| | CUHK01<br>VIPeRPRID<br>(N=871/485)t |
| --- | --- |
| SCSP<br>LSSCDL<br>TMA<br>(cid:96)1GL<br>SiameseLSTM | 53.5--<br>42.6--<br>43.8--<br>41.530.1-/50.1<br>42.4-- |
| MetricEnsemble<br>DNS | 45.9--<br>51.140.9-/69.0 | | | IDLA<br>DGD<br>MCP-CNN<br>GatedS-CNN<br>EDM<br>JointLearning<br>CAN | 34.8-65.0/47.5<br>38.664.0*-/66.6<br>47.822.0-/53.7<br>37.8--<br>40.9-86.6/-<br>35.8-72.5/-<br>--81.0/- |
| --- | --- |
| Ours | 56.343.693.2/77.0 | | 1 |
| | CUHK01<br>VIPeRPRID<br>(N=871/485)t |
| --- | --- |
| SCSP<br>LSSCDL<br>TMA<br>(cid:96)1GL<br>SiameseLSTM | 53.5--<br>42.6--<br>43.8--<br>41.530.1-/50.1<br>42.4-- |
| MetricEnsemble<br>DNS | 45.9--<br>51.140.9-/69.0 | | | A | XQDA<br>GOG<br>NFST<br>SCS | LOMO<br>GOG<br>LOMO,KCCA<br>CHS | -<br>-<br>-<br>- | XQDA<br>XQDA<br>NSFT<br>SCS | -<br>-<br>-<br>- |
| --- | --- | --- | --- | --- | --- |
| B | DCNN+<br>X-Corr<br>MTDnet | -<br>-<br>- | DCNN+<br>X-Corr<br>MTDnet | DVM<br>DVM<br>DVM,L2 | -<br>-<br>- |
| C | S-CNN<br>DGD<br>MCP<br>JLM... | 0 |
| | precision | recall | F1-score | support |
| --- | --- | --- | --- | --- |
| negative | 0.63 | 0.50 | 0.56 | 493 |
| neutral | 0.11 | 0.31 | 0.16 | 127 | | | positive | 0.41 | 0.05 | 0.09 | 143 |
| --- | --- | --- | --- | --- |
| avg/total | 0.50 | 0.38 | 0.40 | 763 | | 1 |
| | precision | recall | F1-score | support |
| --- | --- | --- | --- | --- |
| negative | 0.63 | 0.50 | 0.56 | 493 |
| neutral | 0.11 | 0.31 | 0.16 | 127 | | | | avg/total | Positive | Neutral | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Featurecombination | Prec | Recall | F1 | Prec | Recall | F1 | Prec | Recall | F1 | Prec |
| +f1,f2 | 0.57 | 0.45 | 0.47 | 0.32 | 0.43 | 0.37 | 0.25 | 0.57 | 0.35 | 0.72 |
| +f1,f2,f4 | 0.57 ... | 0 |
| | precision | recall | F1-score | support |
| --- | --- | --- | --- | --- |
| negative | 0.63 | 0.50 | 0.56 | 493 |
| neutral | 0.11 | 0.31 | 0.16 | 127 | | | positive | 0.41 | 0.05 | 0.09 | 143 |
| --- | --- | --- | --- | --- |
| avg/total | 0.50 | 0.38 | 0.40 | 763 | | 1 |
| | precision | recall | F1-score | support |
| --- | --- | --- | --- | --- |
| negative | 0.63 | 0.50 | 0.56 | 493 |
| neutral | 0.11 | 0.31 | 0.16 | 127 | | | +f1,f2,f4,f5,f6,f7 | 0.60 | 0.51 | 0.53 | 0.33 | 0.45 | 0.38 | 0.28 | 0.50 | 0.36 | 0.75 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| +f1,f2,f3,f4,f5,f6,f7,f9 | 0.63 | 0.57 | 0.59 | 0.31 | 0.56 | 0.40 | 0.36 | 0.30 | 0.32 | 0.79 |
| +f1,f2,f3,f4,f5,f6,f7,f8,f9 | 0.69 | 0.71 | 0.69 | 0.51 | ... | 0 |
| | n=70000 | n=90000 | n=110000 | n=130000 |
| --- | --- | --- | --- | --- |
| α1<br>β1<br>γ1 | 1.003105865295161<br>4.99550480505<br>1.006973943599736 | 1.004527508419694<br>4.996572933666054<br>1.005569625063884 | 1.005908384957321<br>4.996874637244825<br>1.005525834804714 | 1.004563178701584<br>4.997085464604526<b... | | α2<br>β2<br>γ2 | 1.997899801933102<br>3.00924729807257<br>6.983912371495364 | 1.994761292346172<br>3.006009800104706<br>6.995712237697553 | 1.996505871342539<br>3.003001585321237<br>7.000067186843735 | 1.997080967404208<br>3.001073196705324<br>6.997260635821995 |
| --- | --- | --- | --- | --- |
| α3<br>β3<br>γ3 | 2.9... | 1 |
| | n=70000 | n=90000 | n=110000 | n=130000 |
| --- | --- | --- | --- | --- |
| α1<br>β1<br>γ1 | 1.003105865295161<br>4.99550480505<br>1.006973943599736 | 1.004527508419694<br>4.996572933666054<br>1.005569625063884 | 1.005908384957321<br>4.996874637244825<br>1.005525834804714 | 1.004563178701584<br>4.997085464604526<b... | | β | 5@NDCG | 10@NDCG | 20@NDCG | 40@NDCG |
| --- | --- | --- | --- | --- |
| 0.5 | 0.3885 | 0.2888 | 0.2139 | 0.1478 |
| 1.5 | 0.3392 | 0.2745 | 0.2035 | 0.1370 |
| 2.5 | 0.3392 | 0.2863 | 0.2036 | 0.1379 |
| 3.5 | 0.3392 | 0.2752 | 0.1988 | 0.1362 | | 0 |
| | n=70000 | n=90000 | n=110000 | n=130000 |
| --- | --- | --- | --- | --- |
| α1<br>β1<br>γ1 | 1.003105865295161<br>4.99550480505<br>1.006973943599736 | 1.004527508419694<br>4.996572933666054<br>1.005569625063884 | 1.005908384957321<br>4.996874637244825<br>1.005525834804714 | 1.004563178701584<br>4.997085464604526<b... | | α2<br>β2<br>γ2 | 1.997899801933102<br>3.00924729807257<br>6.983912371495364 | 1.994761292346172<br>3.006009800104706<br>6.995712237697553 | 1.996505871342539<br>3.003001585321237<br>7.000067186843735 | 1.997080967404208<br>3.001073196705324<br>6.997260635821995 |
| --- | --- | --- | --- | --- |
| α3<br>β3<br>γ3 | 2.9... | 1 |
| | n=70000 | n=90000 | n=110000 | n=130000 |
| --- | --- | --- | --- | --- |
| α1<br>β1<br>γ1 | 1.003105865295161<br>4.99550480505<br>1.006973943599736 | 1.004527508419694<br>4.996572933666054<br>1.005569625063884 | 1.005908384957321<br>4.996874637244825<br>1.005525834804714 | 1.004563178701584<br>4.997085464604526<b... | | 2.5 | 0.3392 | 0.2863 | 0.2036 | 0.1379 |
| --- | --- | --- | --- | --- |
| 3.5 | 0.3392 | 0.2752 | 0.1988 | 0.1362 | | 0 |
| Method | EER | HTER |
| --- | --- | --- |
| WholeFine-TunedVGG-Face | — | 1.20 |
| EfficientFine-TunedVGG-Face | — | 16.62 |
| PatchBasedHandcraftedApproach | — | 5.0 |
| Fine-TunedVGGFace | 8.40 | 4.30 |
| Lietal. | 2.90 | 6.10 | | | RandomPatchesBasedCNN | 2.50 | 1.25 |
| --- | --- | --- |
| Boulkenafetetal. | 0.40 | 2.90 |
| lsCNNTraditionallyTrained | 0.33 | 1.75 |
| lsCNN | 0.33 | 2.50 | | 1 |
| Method | EER | HTER |
| --- | --- | --- |
| WholeFine-TunedVGG-Face | — | 1.20 |
| EfficientFine-TunedVGG-Face | — | 16.62 |
| PatchBasedHandcraftedApproach | — | 5.0 |
| Fine-TunedVGGFace | 8.40 | 4.30 |
| Lietal. | 2.90 | 6.10 | | | Method | LPBA40 | OASIS | Fetal |
| --- | --- | --- | --- |
| Auto-U-net | 10.03 | 22.85 | 14.11 |
| U-net | 4.57 | 11.36 | 6.87 |
| Auto-2.5D-CNN | 794.42 | 641.26 | 501.73 |
| 2.5D-CNN | 396.23 | 320.12 | 244.9 |
| PCNN | 36.51 | 40.99 | - |
| BET | 2.04 | 1.96 | 1.62 |
| 3dSkullStrip | 130.4 | 119.12 | 82.72 |
| R... | 0 |
| Method | EER | HTER |
| --- | --- | --- |
| WholeFine-TunedVGG-Face | — | 1.20 |
| EfficientFine-TunedVGG-Face | — | 16.62 |
| PatchBasedHandcraftedApproach | — | 5.0 |
| Fine-TunedVGGFace | 8.40 | 4.30 |
| Lietal. | 2.90 | 6.10 |
| RandomPatchesBasedCNN | 2.50 | 1.25 |
| Boulkenafetetal. | 0.40 | 2.90 | | | lsCNNTraditionallyTrained | 0.33 | 1.75 |
| --- | --- | --- |
| lsCNN | 0.33 | 2.50 | | 1 |
| Method | EER | HTER |
| --- | --- | --- |
| WholeFine-TunedVGG-Face | — | 1.20 |
| EfficientFine-TunedVGG-Face | — | 16.62 |
| PatchBasedHandcraftedApproach | — | 5.0 |
| Fine-TunedVGGFace | 8.40 | 4.30 |
| Lietal. | 2.90 | 6.10 |
| RandomPatchesBasedCNN | 2.50 | 1.25 |
| Boulkenafetetal. | 0.40 | 2.90 | | | Robex | 52.10 | 63.25 | - |
| --- | --- | --- | --- |
| HWA | 18.73 | 13.42 | - | | 0 |
| Problem | FirstParam. | SecondParam. |
| --- | --- | --- |
| RAN-k | k∈(1..5:1) | NA |
| RANF-k | k∈(1..5:1) | NA |
| FL-k | k∈(1..5:1) | α∈(0..1:0.1) | | | FCL-k | k∈(1..5:1) | α∈(0..1:0.1) |
| --- | --- | --- |
| WSCN | wf∈(−1..1:0.2) | sf∈(−1..1:0.2) | | 1 |
| Problem | FirstParam. | SecondParam. |
| --- | --- | --- |
| RAN-k | k∈(1..5:1) | NA |
| RANF-k | k∈(1..5:1) | NA |
| FL-k | k∈(1..5:1) | α∈(0..1:0.1) | | | fi | f(0)i | f(1)i | f(1)−f(0)ii | i<br>(cid:80)<br>f(1)−f(0)jj<br>j=1 |
| --- | --- | --- | --- | --- |
| f1 | 3 | 5 | 2 | 2 |
| f2 | 7 | 10 | 3 | 5 |
| f3 | 1 | 8 | 7 | 12 |
| f4 | 4 | 18 | 14 | 26 | | 0 |
| Problem | FirstParam. | SecondParam. |
| --- | --- | --- |
| RAN-k | k∈(1..5:1) | NA |
| RANF-k | k∈(1..5:1) | NA |
| FL-k | k∈(1..5:1) | α∈(0..1:0.1) | | | FCL-k | k∈(1..5:1) | α∈(0..1:0.1) |
| --- | --- | --- |
| WSCN | wf∈(−1..1:0.2) | sf∈(−1..1:0.2) | | 1 |
| Problem | FirstParam. | SecondParam. |
| --- | --- | --- |
| RAN-k | k∈(1..5:1) | NA |
| RANF-k | k∈(1..5:1) | NA |
| FL-k | k∈(1..5:1) | α∈(0..1:0.1) | | | f3 | 1 | 8 | 7 | 12 |
| --- | --- | --- | --- | --- |
| f4 | 4 | 18 | 14 | 26 | | 0 |
| | MetaSDNet-01 | pyMDNet-30 | pyMDNet-15 | pyMDNet-10 | pyMDNet-05 | pyMDNet-03 | pyMDNet-01 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Girl2 | 0.7303 | 0.7339 | 0.7238 | 0.7257 | 0.6038 | 0.5872 | 0.6081 |
| Gym | 0.5068 | 0.5141 | 0.4567 | 0.5176 | 0.4625 | 0.4484 | 0.0254 |
| Human2 | 0.7011 | 0.6262 |... | | Human9 | 0.664 | 0.5661 | 0.5538 | 0.4515 | 0.484 | 0.0073 | 0.0031 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Ironman | 0.4604 | 0.428 | 0.1816 | 0.4418 | 0.0138 | 0.1411 | 0.3368 |
| Jogging-1 | 0.7098 | 0.7711 | 0.7369 | 0.7773 | 0.749 | 0.7217 | 0.4915 |
| Jogging-2 | 0.7389 | 0.7439 | 0.7602 | 0.731 |... | 1 |
| | MetaSDNet-01 | pyMDNet-30 | pyMDNet-15 | pyMDNet-10 | pyMDNet-05 | pyMDNet-03 | pyMDNet-01 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Girl2 | 0.7303 | 0.7339 | 0.7238 | 0.7257 | 0.6038 | 0.5872 | 0.6081 |
| Gym | 0.5068 | 0.5141 | 0.4567 | 0.5176 | 0.4625 | 0.4484 | 0.0254 |
| Human2 | 0.7011 | 0.6262 |... | | Split | Base | Male | Female | M+Skin1 | M+Skin3 |
| --- | --- | --- | --- | --- | --- |
| 1 | 0.7281 | 0.7349 | 0.7542 | 0.7417 | 0.82 |
| 2 | 0.7134 | 0.6756 | 0.8364 | 0.7384 | 0.7728 |
| 3 | 0.6817 | 0.7025 | 0.7001 | 0.74 | 0.7336 |
| 4 | 0.7349 | 0.7309 | 0.7676 | 0.7633 | 0.7683 |
| 5 | 0.6066 | 0.6133 | 0.641... | 0 |
| | MetaSDNet-01 | pyMDNet-30 | pyMDNet-15 | pyMDNet-10 | pyMDNet-05 | pyMDNet-03 | pyMDNet-01 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Girl2 | 0.7303 | 0.7339 | 0.7238 | 0.7257 | 0.6038 | 0.5872 | 0.6081 |
| Gym | 0.5068 | 0.5141 | 0.4567 | 0.5176 | 0.4625 | 0.4484 | 0.0254 |
| Human2 | 0.7011 | 0.6262 |... | | Matrix | 0.279 | 0.4671 | 0.4476 | 0.4724 | 0.4705 | 0.1057 | 0.0705 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Mhyang | 0.7521 | 0.8094 | 0.8147 | 0.7603 | 0.6258 | 0.6084 | 0.674 |
| MotorRolling | 0.5839 | 0.5833 | 0.5851 | 0.5976 | 0.5738 | 0.1283 | 0.2398 |
| MountainBike | 0.7652 | 0.7172 | 0.7366 | ... | 1 |
| | MetaSDNet-01 | pyMDNet-30 | pyMDNet-15 | pyMDNet-10 | pyMDNet-05 | pyMDNet-03 | pyMDNet-01 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Girl2 | 0.7303 | 0.7339 | 0.7238 | 0.7257 | 0.6038 | 0.5872 | 0.6081 |
| Gym | 0.5068 | 0.5141 | 0.4567 | 0.5176 | 0.4625 | 0.4484 | 0.0254 |
| Human2 | 0.7011 | 0.6262 |... | | 8 | 0.6561 | 0.6875 | 0.616 | 0.7648 | 0.8001 |
| --- | --- | --- | --- | --- | --- |
| 9 | 0.6531 | 0.6845 | 0.7939 | 0.7391 | 0.7095 |
| 10 | 0.6645 | 0.6907 | 0.6875 | 0.7296 | 0.7504 |
| Average | 0.68449 | 0.69579 | 0.72846 | 0.73412 | 0.75711 | | 0 |
| | µ | ψ | ω | τ |
| --- | --- | --- | --- | --- |
| HPvsPEO | 0.916 | 0.211 | 0.616 | 0.069 |
| HPvsLIN | 0.549 | 0.017 | 0.226 | 0.07 |
| HPvsGA | <0.001 | 0.064 | 0.988 | 0.09 |
| PEOvsLIN | 0.618 | 0.178 | 0.243 | 0.525 | | | PEOvsGA | <0.001 | 0.434 | 0.471 | 0.129 |
| --- | --- | --- | --- | --- |
| LINvsGA | <0.001 | 0.471 | 0.465 | 0.458 | | 1 |
| | µ | ψ | ω | τ |
| --- | --- | --- | --- | --- |
| HPvsPEO | 0.916 | 0.211 | 0.616 | 0.069 |
| HPvsLIN | 0.549 | 0.017 | 0.226 | 0.07 |
| HPvsGA | <0.001 | 0.064 | 0.988 | 0.09 |
| PEOvsLIN | 0.618 | 0.178 | 0.243 | 0.525 | | | network | τ(G) | σ(G) | θ(G) |
| --- | --- | --- | --- |
| cithepph | 0.22 | 0.56 | 0.37 |
| cithepth | 0.2 | 0.53 | 0.36 |
| colastroph | 0.24 | 0.51 | 0.49 |
| colcondmat | 0.37 | 0.64 | 0.76 |
| colgrqc | 0.44 | 0.79 | 0.89 |
| colhepph | 0.26 | 0.58 | 0.7 |
| colhepth | 0.39 | 0.69 | 0.83 |
| emailenron | 0.21 | ... | 0 |
| | µ | ψ | ω | τ |
| --- | --- | --- | --- | --- |
| HPvsPEO | 0.916 | 0.211 | 0.616 | 0.069 |
| HPvsLIN | 0.549 | 0.017 | 0.226 | 0.07 |
| HPvsGA | <0.001 | 0.064 | 0.988 | 0.09 | | | PEOvsLIN | 0.618 | 0.178 | 0.243 | 0.525 |
| --- | --- | --- | --- | --- |
| PEOvsGA | <0.001 | 0.434 | 0.471 | 0.129 |
| LINvsGA | <0.001 | 0.471 | 0.465 | 0.458 | | 1 |
| | µ | ψ | ω | τ |
| --- | --- | --- | --- | --- |
| HPvsPEO | 0.916 | 0.211 | 0.616 | 0.069 |
| HPvsLIN | 0.549 | 0.017 | 0.226 | 0.07 |
| HPvsGA | <0.001 | 0.064 | 0.988 | 0.09 | | | p2p30 | 0.24 | 0.5 | 0.53 |
| --- | --- | --- | --- |
| p2p31 | 0.25 | 0.5 | 0.52 |
| roadnetca | 0.67 | 0.99 | 0.98 |
| roadnetpa | 0.66 | 0.99 | 0.98 |
| roadnettx | 0.67 | 0.99 | 0.98 | | 0 |
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