premise string | hypothesis string | label int64 |
|---|---|---|
| GrowsU | rowweights |
| --- | --- |
| [11110000] | 4 |
| [11001100] | 4 | | | [10101010] | 4 |
| --- | --- |
| [11111111] | 8 | | 1 |
| GrowsU | rowweights |
| --- | --- |
| [11110000] | 4 |
| [11001100] | 4 | | | n | SizeofAn | n | SizeofAn |
| --- | --- | --- | --- |
| 0 | 16 | 8 | 3463008 |
| 1 | 240 | 9 | 2835240 |
| 2 | 1840 | 10 | 1337520 |
| 3 | 17776 | 11 | 855576 |
| 4 | 74952 | 12 | 170592 |
| 5 | 223992 | 13 | 72216 |
| 6 | 360540 | 14 | 42456 |
| 7 | 1110864 | 15 | 23424 | | 0 |
| GrowsU | rowweights |
| --- | --- |
| [11110000] | 4 | | | [11001100] | 4 |
| --- | --- |
| [10101010] | 4 |
| [11111111] | 8 | | 1 |
| GrowsU | rowweights |
| --- | --- |
| [11110000] | 4 | | | 3 | 17776 | 11 | 855576 |
| --- | --- | --- | --- |
| 4 | 74952 | 12 | 170592 |
| 5 | 223992 | 13 | 72216 |
| 6 | 360540 | 14 | 42456 |
| 7 | 1110864 | 15 | 23424 | | 0 |
| Strategy | RMSE±STD | Time | Nb | µ |
| --- | --- | --- | --- | --- |
| SK-Hype | 0.3279±0.1596 | 0.2145 | 211 | - | | | GKKM | 0.3269±0.1594 | 0.6759 | 7 | 0.9220 |
| --- | --- | --- | --- | --- |
| M=5,µ=0.2500,σ=0.04500 | | | | |
| CCBS<br>GCBS | 0.3427±0.1751<br>0.3446±0.1767 | 0.0606<br>0.0209 | 6<br>6 | 0.2461<br>0.2439 |
| M=10,µ=0.1111,σ=0.02010 | | | | |
| CCBS<br>GCBS | 0.3361±0.1686<br>0.3428±0.1745 | 0.0671<br>0.0142 | 12<br>9 | 0.1101<br>0.0840 |
| M=20,µ=0.0526,σ=0.01040 | | | | |
| CCBS<br>GCBS | 0.3327±0.1647<br>0.3361±0.1680 | 0.3483<br>0.0106 | 21<br>19 | 0.0514<br>0.0518 |
| M=30,µ=0.0345,σ=0.00710 | | | | |
| CCBS<br>GCBS | 0.3318±0.1637<br>0.3354±0.1669 | 3.6450<br>0.0132 | 28<br>23 | 0.0331<br>0.0336 | | 1 |
| Strategy | RMSE±STD | Time | Nb | µ |
| --- | --- | --- | --- | --- |
| SK-Hype | 0.3279±0.1596 | 0.2145 | 211 | - | | | Strategy | RMSE±STD | Time | Nb | µ |
| --- | --- | --- | --- | --- |
| SK-Hype | 0.0442±0.0011 | 0.2499 | 211 | - |
| GKKM | 0.1883±0.0317 | 1.8460 | 14 | 0.7969 |
| M=5,µ=0.2500,σ=0.10340 | | | | |
| CCBS<br>GCBS | 0.2045±0.0375<br>0.2441±0.0500 | 0.1001<br>0.0374 | 7<br>5 | 0.2490<br>0.2097 |
| M=10,µ=0.1111,σ=0.05240 | | | | |
| CCBS<br>GCBS | 0.1430±0.0192<br>0.1505±0.0209 | 0.0702<br>0.0191 | 14<br>13 | 0.1079<br>0.1078 |
| M=20,µ=0.0526,σ=0.02730 | | | | |
| CCBS<br>GCBS | 0.0907±0.0069<br>0.0941±0.0081 | 0.2874<br>0.0245 | 24<br>21 | 0.0517<br>0.0492 |
| M=30,µ=0.0345,σ=0.01820 | | | | |
| CCBS<br>GCBS | 0.0705±0.0035<br>0.0674±0.0034 | 0.6403<br>0.0162 | 34<br>32 | 0.0339<br>0.0331 | | 0 |
| Strategy | RMSE±STD | Time | Nb | µ |
| --- | --- | --- | --- | --- |
| SK-Hype | 0.3279±0.1596 | 0.2145 | 211 | - |
| GKKM | 0.3269±0.1594 | 0.6759 | 7 | 0.9220 |
| M=5,µ=0.2500,σ=0.04500 | | | | |
| CCBS<br>GCBS | 0.3427±0.1751<br>0.3446±0.1767 | 0.0606<br>0.0209 | 6<br>6 | 0.2461<br>0.2439 |
| M=10,µ=0.1111,σ=0.02010 | | | | |
| CCBS<br>GCBS | 0.3361±0.1686<br>0.3428±0.1745 | 0.0671<br>0.0142 | 12<br>9 | 0.1101<br>0.0840 | | | M=20,µ=0.0526,σ=0.01040 | | | | |
| --- | --- | --- | --- | --- |
| CCBS<br>GCBS | 0.3327±0.1647<br>0.3361±0.1680 | 0.3483<br>0.0106 | 21<br>19 | 0.0514<br>0.0518 |
| M=30,µ=0.0345,σ=0.00710 | | | | |
| CCBS<br>GCBS | 0.3318±0.1637<br>0.3354±0.1669 | 3.6450<br>0.0132 | 28<br>23 | 0.0331<br>0.0336 | | 1 |
| Strategy | RMSE±STD | Time | Nb | µ |
| --- | --- | --- | --- | --- |
| SK-Hype | 0.3279±0.1596 | 0.2145 | 211 | - |
| GKKM | 0.3269±0.1594 | 0.6759 | 7 | 0.9220 |
| M=5,µ=0.2500,σ=0.04500 | | | | |
| CCBS<br>GCBS | 0.3427±0.1751<br>0.3446±0.1767 | 0.0606<br>0.0209 | 6<br>6 | 0.2461<br>0.2439 |
| M=10,µ=0.1111,σ=0.02010 | | | | |
| CCBS<br>GCBS | 0.3361±0.1686<br>0.3428±0.1745 | 0.0671<br>0.0142 | 12<br>9 | 0.1101<br>0.0840 | | | M=10,µ=0.1111,σ=0.05240 | | | | |
| --- | --- | --- | --- | --- |
| CCBS<br>GCBS | 0.1430±0.0192<br>0.1505±0.0209 | 0.0702<br>0.0191 | 14<br>13 | 0.1079<br>0.1078 |
| M=20,µ=0.0526,σ=0.02730 | | | | |
| CCBS<br>GCBS | 0.0907±0.0069<br>0.0941±0.0081 | 0.2874<br>0.0245 | 24<br>21 | 0.0517<br>0.0492 |
| M=30,µ=0.0345,σ=0.01820 | | | | |
| CCBS<br>GCBS | 0.0705±0.0035<br>0.0674±0.0034 | 0.6403<br>0.0162 | 34<br>32 | 0.0339<br>0.0331 | | 0 |
| Method | Lena |
| --- | --- |
| Bilinear | 30.13 |
| Bicubic | 31.34 | | | NEDI | 34.10 |
| --- | --- |
| WZP-Haar | 31.46 |
| WZP-Db.9/7 | 34.45 |
| Careyetal. | 34.48 |
| HMM | 34.52 |
| HMM-SR | 34.61 |
| WZP-CS | 34.93 |
| SAI | 34.74 |
| Iterative(2iter.) | 35.25 |
| Iterative(10iter.) | 37.39 |
| Hybrid(2iter.and1mod.) | 37.12 |
| Opt.Hybrid(2iter.and1mod.) | 37.41 | | 1 |
| Method | Lena |
| --- | --- |
| Bilinear | 30.13 |
| Bicubic | 31.34 | | | Methods | Accuracy | | |
| --- | --- | --- | --- |
| | 1/3 | 2/3 | cross |
| HOJ3D | 0.962 | 0.971 | 0.789 |
| HMM+DBM | - | - | 0.820 |
| EigenJoints | 0.958 | 0.977 | 0.823 |
| HMM+GMM(ourimplementation) | 0.861 | 0.929 | 0.825 |
| ActionletEnsemble(skeletondata) | - | - | 0.882 |
| SkeletalQuads | - | - | 0.898 |
| LDS | - | - | 0.900 |
| Cov3DJ | - | - | 0.905 |
| Our | 0.943 | 0.983 | 0.905 |
| FSFJ3D | - | - | 0.909 |
| KPLS | - | - | 0.923 | | 0 |
| Method | Lena |
| --- | --- |
| Bilinear | 30.13 |
| Bicubic | 31.34 |
| NEDI | 34.10 |
| WZP-Haar | 31.46 |
| WZP-Db.9/7 | 34.45 |
| Careyetal. | 34.48 |
| HMM | 34.52 |
| HMM-SR | 34.61 |
| WZP-CS | 34.93 |
| SAI | 34.74 | | | Iterative(2iter.) | 35.25 |
| --- | --- |
| Iterative(10iter.) | 37.39 |
| Hybrid(2iter.and1mod.) | 37.12 |
| Opt.Hybrid(2iter.and1mod.) | 37.41 | | 1 |
| Method | Lena |
| --- | --- |
| Bilinear | 30.13 |
| Bicubic | 31.34 |
| NEDI | 34.10 |
| WZP-Haar | 31.46 |
| WZP-Db.9/7 | 34.45 |
| Careyetal. | 34.48 |
| HMM | 34.52 |
| HMM-SR | 34.61 |
| WZP-CS | 34.93 |
| SAI | 34.74 | | | FSFJ3D | - | - | 0.909 |
| --- | --- | --- | --- |
| KPLS | - | - | 0.923 | | 0 |
| V | H | E | Train,Val,Test | Train,Val,Test |
| --- | --- | --- | --- | --- |
| 10 | 128 | 114 | 9k,1k,10k | 0.9744,0.9952,0.9956 |
| 100 | 128 | 200 | 9k,1k,10k | 0.6370,0.5003,0.4996 | | | 100 | 128 | 82 | 135k,15k,10k | 0.9882,0.9907,0.9906 |
| --- | --- | --- | --- | --- |
| 100 | 256 | 62 | 135k,15k,10k | 0.9886,0.9965,0.9969 |
| 1000 | 256 | 127 | 135k,15k,10k | 0.9069,0.7958,0.7971 | | 1 |
| V | H | E | Train,Val,Test | Train,Val,Test |
| --- | --- | --- | --- | --- |
| 10 | 128 | 114 | 9k,1k,10k | 0.9744,0.9952,0.9956 |
| 100 | 128 | 200 | 9k,1k,10k | 0.6370,0.5003,0.4996 | | | V | H | E | Data | Train,Val,Test |
| --- | --- | --- | --- | --- |
| 10 | 128 | 180 | 9k,1k,10k | 0.9635,0.9172,0.9150 |
| 100 | 128 | 200 | 9k,1k,10k | 0.7392,0.5472,0.5488 |
| 100 | 128 | 61 | 135k,15k,10k | 0.9927,0.9911,0.9912 |
| 100 | 256 | 40 | 135k,15k,10k | 0.9974,0.9997,0.9975 |
| 1000 | 256 | 75 | 135k,15k,10k | 0.9868,0.9884,0.9885 | | 0 |
| V | H | E | Train,Val,Test | Train,Val,Test |
| --- | --- | --- | --- | --- |
| 10 | 128 | 114 | 9k,1k,10k | 0.9744,0.9952,0.9956 | | | 100 | 128 | 200 | 9k,1k,10k | 0.6370,0.5003,0.4996 |
| --- | --- | --- | --- | --- |
| 100 | 128 | 82 | 135k,15k,10k | 0.9882,0.9907,0.9906 |
| 100 | 256 | 62 | 135k,15k,10k | 0.9886,0.9965,0.9969 |
| 1000 | 256 | 127 | 135k,15k,10k | 0.9069,0.7958,0.7971 | | 1 |
| V | H | E | Train,Val,Test | Train,Val,Test |
| --- | --- | --- | --- | --- |
| 10 | 128 | 114 | 9k,1k,10k | 0.9744,0.9952,0.9956 | | | 100 | 256 | 40 | 135k,15k,10k | 0.9974,0.9997,0.9975 |
| --- | --- | --- | --- | --- |
| 1000 | 256 | 75 | 135k,15k,10k | 0.9868,0.9884,0.9885 | | 0 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames |
| π | 1in5 | Commoninmath | | | $ | 4in5 | Usedinbusiness |
| --- | --- | --- |
| Ψ | 1in40,000 | Unexplainedusage | | 1 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames |
| π | 1in5 | Commoninmath | | | Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames |
| π | 1in5 | Commoninmath |
| $ | 4in5 | Usedinbusiness |
| Ψ | 1in40,000 | Unexplainedusage | | 0 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames | | | π | 1in5 | Commoninmath |
| --- | --- | --- |
| $ | 4in5 | Usedinbusiness |
| Ψ | 1in40,000 | Unexplainedusage | | 1 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames | | | π | 1in5 | Commoninmath |
| --- | --- | --- |
| $ | 4in5 | Usedinbusiness |
| Ψ | 1in40,000 | Unexplainedusage | | 0 |
| \|A\| | \|T\| | \|S\| | DSA | ICG-Max-Sum |
| --- | --- | --- | --- | --- |
| AcyclicGraphs | | | | | | | 20 | 40 | 25 | 5973.65 | 355.49 |
| --- | --- | --- | --- | --- |
| 20 | 40 | 50 | 2567.29 | 446.51 |
| 100 | 200 | 25 | 23339.31 | 475.67 |
| 100 | 200 | 50 | 17528.18 | 965.22 |
| CyclicGraphs | | | | |
| 5 | 10 | 25 | 797.83 | 48.91 |
| 5 | 10 | 50 | 848.94 | 926.02 |
| 7 | 14 | 25 | 2093.86 | 1247.07 |
| 7 | 14 | 50 | 1646.29 | 1651.56 | | 1 |
| \|A\| | \|T\| | \|S\| | DSA | ICG-Max-Sum |
| --- | --- | --- | --- | --- |
| AcyclicGraphs | | | | | | | Graph | n | LB1 | LB2 | Opt |
| --- | --- | --- | --- | --- |
| TinaDiscal | 11 | 0.31 | 0.86 | 12 |
| jg1009 | 9 | 1.55 | 1.72 | 16 |
| jg1011 | 11 | 1.48 | 0.94 | 24 |
| Stranke94 | 10 | 1.76 | 1.77 | 24 |
| Hamrle1 | 32 | -1.93 | 1.12 | 17 |
| 4x5t | 20 | -21.71 | 5.43 | 28 |
| 8x5t | 40 | -16.16 | 2.91 | 33 |
| t050 | 30 | 0.90 | 18.54 | 397 |
| 2x17m | 34 | 1.33 | 1.27 | 316 |
| s090 | 60 | -9.84 | 13.10 | 238 | | 0 |
| \|A\| | \|T\| | \|S\| | DSA | ICG-Max-Sum |
| --- | --- | --- | --- | --- |
| AcyclicGraphs | | | | | | | 20 | 40 | 25 | 5973.65 | 355.49 |
| --- | --- | --- | --- | --- |
| 20 | 40 | 50 | 2567.29 | 446.51 |
| 100 | 200 | 25 | 23339.31 | 475.67 |
| 100 | 200 | 50 | 17528.18 | 965.22 |
| CyclicGraphs | | | | |
| 5 | 10 | 25 | 797.83 | 48.91 |
| 5 | 10 | 50 | 848.94 | 926.02 |
| 7 | 14 | 25 | 2093.86 | 1247.07 |
| 7 | 14 | 50 | 1646.29 | 1651.56 | | 1 |
| \|A\| | \|T\| | \|S\| | DSA | ICG-Max-Sum |
| --- | --- | --- | --- | --- |
| AcyclicGraphs | | | | | | | t050 | 30 | 0.90 | 18.54 | 397 |
| --- | --- | --- | --- | --- |
| 2x17m | 34 | 1.33 | 1.27 | 316 |
| s090 | 60 | -9.84 | 13.10 | 238 | | 0 |
| Method | testBLEUscore(ntst14) |
| --- | --- |
| Bahdanauetal. | 28.45 |
| BaselineSystem | 33.30 |
| SingleforwardLSTM,beamsize12 | 26.17 | | | SinglereversedLSTM,beamsize12 | 30.59 |
| --- | --- |
| Ensembleof5reversedLSTMs,beamsize1 | 33.00 |
| Ensembleof2reversedLSTMs,beamsize12 | 33.27 |
| Ensembleof5reversedLSTMs,beamsize2 | 34.50 |
| Ensembleof5reversedLSTMs,beamsize12 | 34.81 | | 1 |
| Method | testBLEUscore(ntst14) |
| --- | --- |
| Bahdanauetal. | 28.45 |
| BaselineSystem | 33.30 |
| SingleforwardLSTM,beamsize12 | 26.17 | | | Methods | Depth |
| --- | --- |
| HOG | 32.24 |
| SuperNormalVector | 31.82 |
| HON4D | 30.56 |
| LieGroup | 50.08 |
| SkeletalQuads | 38.62 |
| FTPDynamicSkeletons | 60.23 |
| HBRNN-L | 59.07 |
| 2LayerP-LSTM | 62.93 |
| ShuffleandLearn | 47.5 |
| Ourmethod(Unsupervisedtraining) | 66.2 | | 0 |
| Method | testBLEUscore(ntst14) |
| --- | --- |
| Bahdanauetal. | 28.45 |
| BaselineSystem | 33.30 |
| SingleforwardLSTM,beamsize12 | 26.17 |
| SinglereversedLSTM,beamsize12 | 30.59 |
| Ensembleof5reversedLSTMs,beamsize1 | 33.00 |
| Ensembleof2reversedLSTMs,beamsize12 | 33.27 | | | Ensembleof5reversedLSTMs,beamsize2 | 34.50 |
| --- | --- |
| Ensembleof5reversedLSTMs,beamsize12 | 34.81 | | 1 |
| Method | testBLEUscore(ntst14) |
| --- | --- |
| Bahdanauetal. | 28.45 |
| BaselineSystem | 33.30 |
| SingleforwardLSTM,beamsize12 | 26.17 |
| SinglereversedLSTM,beamsize12 | 30.59 |
| Ensembleof5reversedLSTMs,beamsize1 | 33.00 |
| Ensembleof2reversedLSTMs,beamsize12 | 33.27 | | | HON4D | 30.56 |
| --- | --- |
| LieGroup | 50.08 |
| SkeletalQuads | 38.62 |
| FTPDynamicSkeletons | 60.23 |
| HBRNN-L | 59.07 |
| 2LayerP-LSTM | 62.93 |
| ShuffleandLearn | 47.5 |
| Ourmethod(Unsupervisedtraining) | 66.2 | | 0 |
| EvolutionaryNetwork | | | | | |
| --- | --- | --- | --- | --- | --- |
| m×n | b<10 | b<10 | b<10 | b<10 | b<10 | | | 32×32∼10 | 3 | 6 | 8 | 11 | 13 |
| --- | --- | --- | --- | --- | --- |
| 100×100∼10 | 3 | 6 | 9 | 11 | 14 |
| 320×320∼10 | 3 | 6 | 9 | 11 | 14 |
| 1000×1000∼10 | 3 | 6 | 9 | 11 | 14 | | 1 |
| EvolutionaryNetwork | | | | | |
| --- | --- | --- | --- | --- | --- |
| m×n | b<10 | b<10 | b<10 | b<10 | b<10 | | | Fixednetworks<br>−1−5<br>Configurationofevolutionarynetworkwhenitreaches:(i)b<10,(ii)b<10. | | | | | |
| --- | --- | --- | --- | --- | --- |
| m×n | b<10 | b<10 | b<10 | b<10 | b<10 |
| 32×32(i) | 2 | 5 | 8 | 12 | 16 |
| 320×320(i) | 2 | 5 | 9 | 13 | 17 |
| 32×32(ii) | 2 | 4 | 7 | 9 | 12 |
| 320×320(ii) | 2 | 5 | 7 | 10 | 12 | | 0 |
| EvolutionaryNetwork | | | | | |
| --- | --- | --- | --- | --- | --- |
| m×n | b<10 | b<10 | b<10 | b<10 | b<10 | | | 32×32∼10 | 3 | 6 | 8 | 11 | 13 |
| --- | --- | --- | --- | --- | --- |
| 100×100∼10 | 3 | 6 | 9 | 11 | 14 |
| 320×320∼10 | 3 | 6 | 9 | 11 | 14 |
| 1000×1000∼10 | 3 | 6 | 9 | 11 | 14 | | 1 |
| EvolutionaryNetwork | | | | | |
| --- | --- | --- | --- | --- | --- |
| m×n | b<10 | b<10 | b<10 | b<10 | b<10 | | | 320×320(i) | 2 | 5 | 9 | 13 | 17 |
| --- | --- | --- | --- | --- | --- |
| 32×32(ii) | 2 | 4 | 7 | 9 | 12 |
| 320×320(ii) | 2 | 5 | 7 | 10 | 12 | | 0 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 | | | -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| --- |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 |
| -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 |
| -classe1890(attendus=197,ramenes=81.00,corrects=7.00)<br>rappel=0.036precision=0.086f-mesure=0.050 |
| -classe1900(attendus=203,ramenes=153.00,corrects=14.00)<br>rappel=0.069precision=0.092f-mesure=0.079 |
| -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 1 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 | | | -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 |
| -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 |
| -classe1890(attendus=197,ramenes=81.00,corrects=7.00)<br>rappel=0.036precision=0.086f-mesure=0.050 |
| -classe1900(attendus=203,ramenes=153.00,corrects=14.00)<br>rappel=0.069precision=0.092f-mesure=0.079 |
| -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 0 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 | | | -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| --- |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 |
| -classe1890(attendus=197,ramenes=81.00,corrects=7.00)<br>rappel=0.036precision=0.086f-mesure=0.050 |
| -classe1900(attendus=203,ramenes=153.00,corrects=14.00)<br>rappel=0.069precision=0.092f-mesure=0.079 |
| -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 1 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 | | | -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| --- |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 0 |
| Episode | Ranking<br>CNN | Hypercolumn<br>Ranking |
| --- | --- | --- |
| FromPoletoPole | 8.23 | 4.10 |
| Mountains | 12.08 | 7.94 |
| FreshWater | 12.36 | 8.11 |
| Caves | 9.98 | 8.76 |
| Deserts | 13.90 | 9.35 |
| IceWorlds | 6.62 | 4.33 |
| GreatPlains | 10.92 | 9.63 | | | Jungles | 12.28 | 7.43 |
| --- | --- | --- |
| ShallowSeas | 10.91 | 6.22 |
| SeasonalForests | 9.47 | 4.82 |
| OceanDeep | 10.73 | 5.75 |
| Average | 10.68 | 6.95 | | 1 |
| Episode | Ranking<br>CNN | Hypercolumn<br>Ranking |
| --- | --- | --- |
| FromPoletoPole | 8.23 | 4.10 |
| Mountains | 12.08 | 7.94 |
| FreshWater | 12.36 | 8.11 |
| Caves | 9.98 | 8.76 |
| Deserts | 13.90 | 9.35 |
| IceWorlds | 6.62 | 4.33 |
| GreatPlains | 10.92 | 9.63 | | | Episode | Ranking<br>CNN | Hypercolumn<br>Ranking |
| --- | --- | --- |
| FromPoletoPole | 8.23 | 4.10 |
| Mountains | 12.08 | 7.94 |
| FreshWater | 12.36 | 8.11 |
| Caves | 9.98 | 8.76 |
| Deserts | 13.90 | 9.35 |
| IceWorlds | 6.62 | 4.33 |
| GreatPlains | 10.92 | 9.63 |
| Jungles | 12.28 | 7.43 |
| ShallowSeas | 10.91 | 6.22 |
| SeasonalForests | 9.47 | 4.82 |
| OceanDeep | 10.73 | 5.75 |
| Average | 10.68 | 6.95 | | 0 |
| Episode | Ranking<br>CNN | Hypercolumn<br>Ranking |
| --- | --- | --- |
| FromPoletoPole | 8.23 | 4.10 |
| Mountains | 12.08 | 7.94 | | | FreshWater | 12.36 | 8.11 |
| --- | --- | --- |
| Caves | 9.98 | 8.76 |
| Deserts | 13.90 | 9.35 |
| IceWorlds | 6.62 | 4.33 |
| GreatPlains | 10.92 | 9.63 |
| Jungles | 12.28 | 7.43 |
| ShallowSeas | 10.91 | 6.22 |
| SeasonalForests | 9.47 | 4.82 |
| OceanDeep | 10.73 | 5.75 |
| Average | 10.68 | 6.95 | | 1 |
| Episode | Ranking<br>CNN | Hypercolumn<br>Ranking |
| --- | --- | --- |
| FromPoletoPole | 8.23 | 4.10 |
| Mountains | 12.08 | 7.94 | | | FreshWater | 12.36 | 8.11 |
| --- | --- | --- |
| Caves | 9.98 | 8.76 |
| Deserts | 13.90 | 9.35 |
| IceWorlds | 6.62 | 4.33 |
| GreatPlains | 10.92 | 9.63 |
| Jungles | 12.28 | 7.43 |
| ShallowSeas | 10.91 | 6.22 |
| SeasonalForests | 9.47 | 4.82 |
| OceanDeep | 10.73 | 5.75 |
| Average | 10.68 | 6.95 | | 0 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 6.07K | 5.75 | 4.42 | 3.57 | | | MCCo | 5.21 | 6.38 | 6.00 | 3.75 |
| --- | --- | --- | --- | --- |
| MCCf | 4.32 | 6.00 | 6.15 | 2.68 |
| MCCe | 4.25 | 6.78 | 6.72 | 3.20 |
| MCCco | 3.85 | 5.35 | 3.78 | 2.38 |
| MCCcf | 4.00 | 5.71 | 5.63 | 2.39 |
| MCCce | 4.24 | 6.46 | 6.74 | 3.07 | | 1 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 6.07K | 5.75 | 4.42 | 3.57 | | | Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 20.1K | 11.6 | 12.6 | 9.75 |
| MCCo | 13.2 | 10.4 | 12.4 | 5.71 |
| MCCf | 11.8 | 9.21 | 9.78 | 5.25 |
| MCCe | 11.9 | 8.28 | 8.71 | 5.71 |
| MCCco | 12.9 | 10.9 | 11.92 | 5.92 |
| MCCcf | 13.1 | 10.03 | 11.92 | 5.57 |
| MCCce | 13.4 | 10.85 | 13.57 | 7.64 | | 0 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 6.07K | 5.75 | 4.42 | 3.57 |
| MCCo | 5.21 | 6.38 | 6.00 | 3.75 |
| MCCf | 4.32 | 6.00 | 6.15 | 2.68 |
| MCCe | 4.25 | 6.78 | 6.72 | 3.20 |
| MCCco | 3.85 | 5.35 | 3.78 | 2.38 | | | MCCcf | 4.00 | 5.71 | 5.63 | 2.39 |
| --- | --- | --- | --- | --- |
| MCCce | 4.24 | 6.46 | 6.74 | 3.07 | | 1 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 6.07K | 5.75 | 4.42 | 3.57 |
| MCCo | 5.21 | 6.38 | 6.00 | 3.75 |
| MCCf | 4.32 | 6.00 | 6.15 | 2.68 |
| MCCe | 4.25 | 6.78 | 6.72 | 3.20 |
| MCCco | 3.85 | 5.35 | 3.78 | 2.38 | | | MCCo | 13.2 | 10.4 | 12.4 | 5.71 |
| --- | --- | --- | --- | --- |
| MCCf | 11.8 | 9.21 | 9.78 | 5.25 |
| MCCe | 11.9 | 8.28 | 8.71 | 5.71 |
| MCCco | 12.9 | 10.9 | 11.92 | 5.92 |
| MCCcf | 13.1 | 10.03 | 11.92 | 5.57 |
| MCCce | 13.4 | 10.85 | 13.57 | 7.64 | | 0 |
| Layer<br>(h) | Input<br>Size | Window<br>Size(l) | Filters<br>(f) | Pool<br>Size(p) |
| --- | --- | --- | --- | --- |
| 1 | 150×70 | 7 | 256 | 3 |
| 2 | 42×256 | 7 | 256 | 3 | | | 3 | 14×256 | 3 | 256 | N/A |
| --- | --- | --- | --- | --- |
| 4 | 12×256 | 3 | 256 | N/A |
| 5 | 10×256 | 3 | 256 | N/A | | 1 |
| Layer<br>(h) | Input<br>Size | Window<br>Size(l) | Filters<br>(f) | Pool<br>Size(p) |
| --- | --- | --- | --- | --- |
| 1 | 150×70 | 7 | 256 | 3 |
| 2 | 42×256 | 7 | 256 | 3 | | | Layer | Input/FilterDimensions | |
| --- | --- | --- |
| Input | 512×512×1 | 512×512×1 |
| Conv1<br>MaxPooling | 8×7×7<br>2×2 | 8×7×7<br>2×2 |
| Conv2<br>MaxPooling | 16×5×5<br>2×2 | 16×5×5<br>2×2 |
| Conv3<br>MaxPooling | 64×3×3<br>2×2 | |
| Conv4<br>MaxPooling | 64×3×3<br>2×2 | |
| FC1 | 2048 | |
| FC2 | 1024 | | | 0 |
| Layer<br>(h) | Input<br>Size | Window<br>Size(l) | Filters<br>(f) | Pool<br>Size(p) |
| --- | --- | --- | --- | --- |
| 1 | 150×70 | 7 | 256 | 3 |
| 2 | 42×256 | 7 | 256 | 3 | | | 3 | 14×256 | 3 | 256 | N/A |
| --- | --- | --- | --- | --- |
| 4 | 12×256 | 3 | 256 | N/A |
| 5 | 10×256 | 3 | 256 | N/A | | 1 |
| Layer<br>(h) | Input<br>Size | Window<br>Size(l) | Filters<br>(f) | Pool<br>Size(p) |
| --- | --- | --- | --- | --- |
| 1 | 150×70 | 7 | 256 | 3 |
| 2 | 42×256 | 7 | 256 | 3 | | | Conv4<br>MaxPooling | 64×3×3<br>2×2 |
| --- | --- |
| FC1 | 2048 |
| FC2 | 1024 | | 0 |
| Action | (MV,MDR) | ValuesofAUandotherderivedfeatures(MV,MR) | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | BMCG | BMC | Head | Hand | Leg | SA | MD | | | Stand | (0,–) | (0,X) | (0,X) | (0,X) | (0,X) | – | (-1,0,1) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Wave | (0,–) | (1,MID) | (0,UP) | (2,UP/MID) | (0,LL) | – | (-1,0,1) |
| Punch | (0,–) | (1,MID) | (1,UP) | (2,UP/MID) | (0,LL) | (0-30) | (-1,0,1) |
| Kick | (0,–) | (1,MID) | (1,UP) | (1,MID) | (0,LL/MID | (0-130) | (-1,0,1) |
| Jump | (2,Y/XY) | (1,MID) | (1,UP) | (1,MID) | (1,LL) | – | (-1,0,1) |
| Run | (2,X/XY) | (1,MID) | (–,–) | (–,–) | (2,LL) | (0-90) | (-1,0,1) |
| Walk | (2,X/XY) | (1,MID) | (–,–) | (–,–) | (2,LL) | (0-60) | (-1,0,1) |
| Turnback | (1,X/XY) | (1,MID) | (1,UP) | (1,MID) | (1,LL) | (0-30) | (-1,0,1) | | 1 |
| Action | (MV,MDR) | ValuesofAUandotherderivedfeatures(MV,MR) | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | BMCG | BMC | Head | Hand | Leg | SA | MD | | | Action | Possibleoffsets |
| --- | --- |
| finish | (0,0) |
| left | (-1,0),(-1,-1),(-1,1) |
| right | (1,0),(1,-1),(1,1) |
| up | (0,1),(-1,1),(1,1) |
| down | (0,-1),(1,-1),(-1,-1) |
| left-up | (-1,1),(-1,0),(0,1) |
| left-down | (-1,-1),(0,-1),(-1,0) |
| right-up | (1,1),(0,1),(1,0) |
| right-down | (1,-1),(1,0),(0,-1) | | 0 |
| Action | (MV,MDR) | ValuesofAUandotherderivedfeatures(MV,MR) | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | BMCG | BMC | Head | Hand | Leg | SA | MD |
| Stand | (0,–) | (0,X) | (0,X) | (0,X) | (0,X) | – | (-1,0,1) |
| Wave | (0,–) | (1,MID) | (0,UP) | (2,UP/MID) | (0,LL) | – | (-1,0,1) |
| Punch | (0,–) | (1,MID) | (1,UP) | (2,UP/MID) | (0,LL) | (0-30) | (-1,0,1) |
| Kick | (0,–) | (1,MID) | (1,UP) | (1,MID) | (0,LL/MID | (0-130) | (-1,0,1) | | | Jump | (2,Y/XY) | (1,MID) | (1,UP) | (1,MID) | (1,LL) | – | (-1,0,1) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Run | (2,X/XY) | (1,MID) | (–,–) | (–,–) | (2,LL) | (0-90) | (-1,0,1) |
| Walk | (2,X/XY) | (1,MID) | (–,–) | (–,–) | (2,LL) | (0-60) | (-1,0,1) |
| Turnback | (1,X/XY) | (1,MID) | (1,UP) | (1,MID) | (1,LL) | (0-30) | (-1,0,1) | | 1 |
| Action | (MV,MDR) | ValuesofAUandotherderivedfeatures(MV,MR) | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | BMCG | BMC | Head | Hand | Leg | SA | MD |
| Stand | (0,–) | (0,X) | (0,X) | (0,X) | (0,X) | – | (-1,0,1) |
| Wave | (0,–) | (1,MID) | (0,UP) | (2,UP/MID) | (0,LL) | – | (-1,0,1) |
| Punch | (0,–) | (1,MID) | (1,UP) | (2,UP/MID) | (0,LL) | (0-30) | (-1,0,1) |
| Kick | (0,–) | (1,MID) | (1,UP) | (1,MID) | (0,LL/MID | (0-130) | (-1,0,1) | | | right-up | (1,1),(0,1),(1,0) |
| --- | --- |
| right-down | (1,-1),(1,0),(0,-1) | | 0 |
| Segmentationtime(seconds) | | | | |
| --- | --- | --- | --- | --- |
| | SVM1 | SVMLast | SDAE1 | SDAELast |
| Opticnerve(L) | 173.4234(±5.4534) | 221.3296(±6.7034) | 0.1915(±0.0124) | 0.2628(±0.0172) |
| Opticnerve(R) | 167.7524(±6.7484) | 214.4560(±9.3614) | 0.1726(±0.0091) | 0.2517(±0.0194) |
| Pituitarygland | 15.5368(±0.7802) | 19.3440(±0.8235) | 0.0536(±0.0066) | 0.0748(±0.0065) | | | Pituitarystalk | 3.0150(±0.1485) | 4.1328(±0.3899) | 0.0146(±0.0018) | 0.0262(±0.0027) |
| --- | --- | --- | --- | --- |
| Chiasm | 5.2022(±0.3214) | 5.8751(±0.5424) | 0.0628(±0.0065) | 0.1315(±0.0124) | | 1 |
| Segmentationtime(seconds) | | | | |
| --- | --- | --- | --- | --- |
| | SVM1 | SVMLast | SDAE1 | SDAELast |
| Opticnerve(L) | 173.4234(±5.4534) | 221.3296(±6.7034) | 0.1915(±0.0124) | 0.2628(±0.0172) |
| Opticnerve(R) | 167.7524(±6.7484) | 214.4560(±9.3614) | 0.1726(±0.0091) | 0.2517(±0.0194) |
| Pituitarygland | 15.5368(±0.7802) | 19.3440(±0.8235) | 0.0536(±0.0066) | 0.0748(±0.0065) | | | DATASET | KNN | SVM | RandomForest |
| --- | --- | --- | --- |
| englishdailabor | 55.5(±1.7) | 58.2(±1.6) | 60.9(±1.7) |
| aisoposntua | 51.7(±4.3) | 59.0(±1.0) | 59.7(±2.5) |
| sentistrengthdigg | 46.0(±1.6) | 51.7(±2.8) | 49.4(±1.0) |
| debate | 40.6(±1.5) | 23.7(±19.8) | 42.6(±1.7) |
| sentistrengthrw | 37.3(±5.0) | 17.3(±14.6) | 34.6(±1.8) | | 0 |
| Segmentationtime(seconds) | | | | |
| --- | --- | --- | --- | --- |
| | SVM1 | SVMLast | SDAE1 | SDAELast |
| Opticnerve(L) | 173.4234(±5.4534) | 221.3296(±6.7034) | 0.1915(±0.0124) | 0.2628(±0.0172) | | | Opticnerve(R) | 167.7524(±6.7484) | 214.4560(±9.3614) | 0.1726(±0.0091) | 0.2517(±0.0194) |
| --- | --- | --- | --- | --- |
| Pituitarygland | 15.5368(±0.7802) | 19.3440(±0.8235) | 0.0536(±0.0066) | 0.0748(±0.0065) |
| Pituitarystalk | 3.0150(±0.1485) | 4.1328(±0.3899) | 0.0146(±0.0018) | 0.0262(±0.0027) |
| Chiasm | 5.2022(±0.3214) | 5.8751(±0.5424) | 0.0628(±0.0065) | 0.1315(±0.0124) | | 1 |
| Segmentationtime(seconds) | | | | |
| --- | --- | --- | --- | --- |
| | SVM1 | SVMLast | SDAE1 | SDAELast |
| Opticnerve(L) | 173.4234(±5.4534) | 221.3296(±6.7034) | 0.1915(±0.0124) | 0.2628(±0.0172) | | | debate | 40.6(±1.5) | 23.7(±19.8) | 42.6(±1.7) |
| --- | --- | --- | --- |
| sentistrengthrw | 37.3(±5.0) | 17.3(±14.6) | 34.6(±1.8) | | 0 |
| CIFAR-10 | NUS-WIDE | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 12bits | 24bits | 32bits | 48bits | 12bits | 24bits | 32bits | 48bits | 12bits | | | 0.162<br>0.131<br>0.121<br>0.138 | 0.169<br>0.135<br>0.126<br>0.141 | 0.172<br>0.133<br>0.120<br>0.146 | 0.175<br>0.130<br>0.120<br>0.150 | 0.452<br>0.433<br>0.403<br>0.413 | 0.468<br>0.426<br>0.421<br>0.413 | 0.472<br>0.426<br>0.426<br>0.424 | 0.477<br>0.423<br>0.441<br>0.431 | 0.544<br>0.531<br>0.499<br>0.569 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.196<br>0.174<br>0.101<br>0.212 | 0.246<br>0.205<br>0.128<br>0.247 | 0.289<br>0.220<br>0.132<br>0.256 | 0.301<br>0.232<br>0.169<br>0.281 | 0.435<br>0.433<br>0.401<br>0.549 | 0.435<br>0.426<br>0.442<br>0.614 | 0.548<br>0.426<br>0.480<br>0.653 | 0.435<br>0.423<br>0.471<br>0.678 | 0.553<br>0.550<br>0.543<br>0.552 |
| 0.185<br>0.160<br>0.401 | 0.218<br>0.164<br>0.512 | 0.248<br>0.166<br>0.531 | 0.263<br>0.168<br>0.558 | 0.383<br>0.422<br>0.675 | 0.401<br>0.448<br>0.690 | 0.403<br>0.480<br>0.714 | 0.412<br>0.493<br>0.728 | 0.501<br>0.553<br>0.683 | | 1 |
| CIFAR-10 | NUS-WIDE | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 12bits | 24bits | 32bits | 48bits | 12bits | 24bits | 32bits | 48bits | 12bits | | | 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 |
| --- | --- | --- |
| 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814·10 | 3219769<br>6427398<br>7<br>1.2827·10 |
| 8<br>4<br>2 | 8.928·10<br>9<br>1.7856·10<br>9<br>3.5712·10 | 8.9394·10<br>9<br>1.7871·10<br>9<br>3.573·10 |
| 8<br>4<br>2 | 1.2497·10<br>9<br>2.4995·10<br>9<br>4.9989·10 | 1.251·10<br>9<br>2.5005·10<br>9<br>4.9995·10 |
| 8 | 6.4582·10 | 6.4651·10 | | 0 |
| CIFAR-10 | NUS-WIDE | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 12bits | 24bits | 32bits | 48bits | 12bits | 24bits | 32bits | 48bits | 12bits |
| 0.162<br>0.131<br>0.121<br>0.138 | 0.169<br>0.135<br>0.126<br>0.141 | 0.172<br>0.133<br>0.120<br>0.146 | 0.175<br>0.130<br>0.120<br>0.150 | 0.452<br>0.433<br>0.403<br>0.413 | 0.468<br>0.426<br>0.421<br>0.413 | 0.472<br>0.426<br>0.426<br>0.424 | 0.477<br>0.423<br>0.441<br>0.431 | 0.544<br>0.531<br>0.499<br>0.569 | | | 0.196<br>0.174<br>0.101<br>0.212 | 0.246<br>0.205<br>0.128<br>0.247 | 0.289<br>0.220<br>0.132<br>0.256 | 0.301<br>0.232<br>0.169<br>0.281 | 0.435<br>0.433<br>0.401<br>0.549 | 0.435<br>0.426<br>0.442<br>0.614 | 0.548<br>0.426<br>0.480<br>0.653 | 0.435<br>0.423<br>0.471<br>0.678 | 0.553<br>0.550<br>0.543<br>0.552 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0.185<br>0.160<br>0.401 | 0.218<br>0.164<br>0.512 | 0.248<br>0.166<br>0.531 | 0.263<br>0.168<br>0.558 | 0.383<br>0.422<br>0.675 | 0.401<br>0.448<br>0.690 | 0.403<br>0.480<br>0.714 | 0.412<br>0.493<br>0.728 | 0.501<br>0.553<br>0.683 | | 1 |
| CIFAR-10 | NUS-WIDE | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 12bits | 24bits | 32bits | 48bits | 12bits | 24bits | 32bits | 48bits | 12bits |
| 0.162<br>0.131<br>0.121<br>0.138 | 0.169<br>0.135<br>0.126<br>0.141 | 0.172<br>0.133<br>0.120<br>0.146 | 0.175<br>0.130<br>0.120<br>0.150 | 0.452<br>0.433<br>0.403<br>0.413 | 0.468<br>0.426<br>0.421<br>0.413 | 0.472<br>0.426<br>0.426<br>0.424 | 0.477<br>0.423<br>0.441<br>0.431 | 0.544<br>0.531<br>0.499<br>0.569 | | | 8<br>4<br>2 | 1.2497·10<br>9<br>2.4995·10<br>9<br>4.9989·10 | 1.251·10<br>9<br>2.5005·10<br>9<br>4.9995·10 |
| --- | --- | --- |
| 8 | 6.4582·10 | 6.4651·10 | | 0 |
| Method | R1mAP |
| --- | --- |
| CAN<br>HP-Net | 48.2424.43<br>76.90- |
| DuATM | 91.4276.62 | | | ST-RNN<br>QAN | 70.6050.70<br>73.7451.70 |
| --- | --- |
| DuATM | 78.7462.26 | | 1 |
| Method | R1mAP |
| --- | --- |
| CAN<br>HP-Net | 48.2424.43<br>76.90- |
| DuATM | 91.4276.62 | | | Method | nC | Easy | Medium | Hard |
| --- | --- | --- | --- | --- |
| MTCNN | - | 0.848 | 0.825 | 0.598 |
| HR-ResNet101 | - | 0.925 | 0.910 | 0.806 |
| APN24+RNet48 | 3 | 0.883 | 0.879 | 0.761 |
| APN24+RNet48+RNet96 | 3 | 0.906 | 0.895 | 0.801 | | 0 |
| Method | R1mAP |
| --- | --- |
| CAN<br>HP-Net | 48.2424.43<br>76.90- |
| DuATM | 91.4276.62 | | | ST-RNN<br>QAN | 70.6050.70<br>73.7451.70 |
| --- | --- |
| DuATM | 78.7462.26 | | 1 |
| Method | R1mAP |
| --- | --- |
| CAN<br>HP-Net | 48.2424.43<br>76.90- |
| DuATM | 91.4276.62 | | | HR-ResNet101 | - | 0.925 | 0.910 | 0.806 |
| --- | --- | --- | --- | --- |
| APN24+RNet48 | 3 | 0.883 | 0.879 | 0.761 |
| APN24+RNet48+RNet96 | 3 | 0.906 | 0.895 | 0.801 | | 0 |
| | TeslaK40t |
| --- | --- |
| GPUchip | GK110BGL |
| Computecapability | 3.5 |
| GPUmemory(GDDR5SGRAM) | 12288MiB |
| Memorybuswidth | 384bits |
| Peakmemoryclockrate | 3004MHz |
| Theoreticalmemorybandwidth | 268.58GiB/s | | | NumberofSMXprocessors | 15 |
| --- | --- |
| Max32-bitregistersperSIMDprocessor | 65536 |
| Maxsharedmemoryperthreadblock | 49152bytes |
| L2cachesize | 1.50MiB | | 1 |
| | TeslaK40t |
| --- | --- |
| GPUchip | GK110BGL |
| Computecapability | 3.5 |
| GPUmemory(GDDR5SGRAM) | 12288MiB |
| Memorybuswidth | 384bits |
| Peakmemoryclockrate | 3004MHz |
| Theoreticalmemorybandwidth | 268.58GiB/s | | | GPUModel | TeslaC2050 | GeForceGT640 |
| --- | --- | --- |
| CUDADriver | 4.2 | 5.0 |
| CUDARuntime | 4.2 | 4.2 |
| CUDACapability | 2.0 | 3.0 |
| GPUArchitecture | FermiGF100 | KeplerGK107 |
| GlobalMemory | 5GB | 2GB |
| SharedMemoryperMP | 48KB | 16KB |
| Registers | 32768 | 65536 |
| WarpSize | 32 | 32 |
| CUDACores | 448 | 384 |
| Multiprocessors(MP) | 14 | 2 |
| TotalSharedMemory | 672KB | 32KB |
| LinuxKernel | 3.3.7-x8664 | 3.5.2-x8664 | | 0 |
| | TeslaK40t |
| --- | --- |
| GPUchip | GK110BGL | | | Computecapability | 3.5 |
| --- | --- |
| GPUmemory(GDDR5SGRAM) | 12288MiB |
| Memorybuswidth | 384bits |
| Peakmemoryclockrate | 3004MHz |
| Theoreticalmemorybandwidth | 268.58GiB/s |
| NumberofSMXprocessors | 15 |
| Max32-bitregistersperSIMDprocessor | 65536 |
| Maxsharedmemoryperthreadblock | 49152bytes |
| L2cachesize | 1.50MiB | | 1 |
| | TeslaK40t |
| --- | --- |
| GPUchip | GK110BGL | | | CUDACores | 448 | 384 |
| --- | --- | --- |
| Multiprocessors(MP) | 14 | 2 |
| TotalSharedMemory | 672KB | 32KB |
| LinuxKernel | 3.3.7-x8664 | 3.5.2-x8664 | | 0 |
| Utility | NE | NSE | RSEforheuristicalgorithm |
| --- | --- | --- | --- |
| Leader1 | 7.07 | 5.06 | 4.97 |
| Leader2 | 1.67 | 4.33 | 4.19 | | | Follower | 1.7 | 2.08 | 2.49 |
| --- | --- | --- | --- |
| Socialutilityoftheleader2andthefollower | 3.37 | 6.41 | 6.68 | | 1 |
| Utility | NE | NSE | RSEforheuristicalgorithm |
| --- | --- | --- | --- |
| Leader1 | 7.07 | 5.06 | 4.97 |
| Leader2 | 1.67 | 4.33 | 4.19 | | | | E–<br>P– | E+<br>P– | E–<br>P+ | E+<br>P+ |
| --- | --- | --- | --- | --- |
| Morph/lexlookup | 0.53 | 0.54 | 0.54 | 0.49 |
| Phrasalparsing | 0.27 | 0.28 | 0.14 | 0.14 |
| Pruning | – | – | 0.57 | 0.56 |
| Fullparsing | 12.42 | 2.61 | 3.04 | 0.26 |
| Preferences | 3.63 | 1.57 | 1.27 | 0.41 |
| TOTAL | 16.85 | 5.00 | 5.57 | 1.86 | | 0 |
| Utility | NE | NSE | RSEforheuristicalgorithm |
| --- | --- | --- | --- |
| Leader1 | 7.07 | 5.06 | 4.97 | | | Leader2 | 1.67 | 4.33 | 4.19 |
| --- | --- | --- | --- |
| Follower | 1.7 | 2.08 | 2.49 |
| Socialutilityoftheleader2andthefollower | 3.37 | 6.41 | 6.68 | | 1 |
| Utility | NE | NSE | RSEforheuristicalgorithm |
| --- | --- | --- | --- |
| Leader1 | 7.07 | 5.06 | 4.97 | | | Phrasalparsing | 0.27 | 0.28 | 0.14 | 0.14 |
| --- | --- | --- | --- | --- |
| Pruning | – | – | 0.57 | 0.56 |
| Fullparsing | 12.42 | 2.61 | 3.04 | 0.26 |
| Preferences | 3.63 | 1.57 | 1.27 | 0.41 |
| TOTAL | 16.85 | 5.00 | 5.57 | 1.86 | | 0 |
| | PDTB-basedDataSet | SEW-basedDataSet |
| --- | --- | --- |
| Source | PennDiscourse<br>TreebankCorpus | SimpleEnglish<br>WikipediaCorpus | | | #ofpairsofarticles | 378 | 1988 |
| --- | --- | --- |
| #ofpositivepairs | 194 | 944 |
| #ofnegativepairs | 184 | 944 |
| DiscourseAnnotation | ManuallyAnnotated | Extractedusing<br>End-to-Endparser | | 1 |
| | PDTB-basedDataSet | SEW-basedDataSet |
| --- | --- | --- |
| Source | PennDiscourse<br>TreebankCorpus | SimpleEnglish<br>WikipediaCorpus | | | LexicalFeatures |
| --- |
| currenttoken/currenttokenandnexttoken<br>lengthoftheDA<br>isdigit?<br>appearinginnextDA?<br>nextDAisapositivefeedback? |
| StructuralFeatures |
| seeTable3 |
| GrammaticalFeatures |
| part-of-speech<br>phrasetype(VP/NP/PP)<br>dependencyrelations |
| OtherFeatures |
| speakerrole<br>topic | | 0 |
| | PDTB-basedDataSet | SEW-basedDataSet |
| --- | --- | --- |
| Source | PennDiscourse<br>TreebankCorpus | SimpleEnglish<br>WikipediaCorpus | | | #ofpairsofarticles | 378 | 1988 |
| --- | --- | --- |
| #ofpositivepairs | 194 | 944 |
| #ofnegativepairs | 184 | 944 |
| DiscourseAnnotation | ManuallyAnnotated | Extractedusing<br>End-to-Endparser | | 1 |
| | PDTB-basedDataSet | SEW-basedDataSet |
| --- | --- | --- |
| Source | PennDiscourse<br>TreebankCorpus | SimpleEnglish<br>WikipediaCorpus | | | OtherFeatures |
| --- |
| speakerrole<br>topic | | 0 |
| Sport | KeyMoments |
| --- | --- |
| TrainingData | |
| 2010NFLDivisionChampionship | 13 |
| 2012PremierLeagueSoccerGames | 21 |
| 2014NHLStanleyCupPlayoffs | 24 |
| 2014NBAPlayoffs | 3 |
| 2014KentuckyDerbyHorseRace | 3 |
| 2014BelmontStakesHorseRace | 3 |
| 2014FIFAWorldCupStagesA+B | 80 |
| TestingData | |
| 2013MLBWorldSeriesGame5 | 7 |
| 2013MLBWorldSeriesGame6 | 8 |
| 2014NFLSuperBowl | 13 | | | 2014FIFAWorldCupThirdPlace | 11 |
| --- | --- |
| 2014FIFAWorldCupFinal | 7 |
| Total | 193 | | 1 |
| Sport | KeyMoments |
| --- | --- |
| TrainingData | |
| 2010NFLDivisionChampionship | 13 |
| 2012PremierLeagueSoccerGames | 21 |
| 2014NHLStanleyCupPlayoffs | 24 |
| 2014NBAPlayoffs | 3 |
| 2014KentuckyDerbyHorseRace | 3 |
| 2014BelmontStakesHorseRace | 3 |
| 2014FIFAWorldCupStagesA+B | 80 |
| TestingData | |
| 2013MLBWorldSeriesGame5 | 7 |
| 2013MLBWorldSeriesGame6 | 8 |
| 2014NFLSuperBowl | 13 | | | Event | TweetCount |
| --- | --- |
| TrainingData | |
| 2010NFLDivisionChampionship | 109,809 |
| 2012PremierLeagueSoccerGames | 1,064,040 |
| 2014NHLStanleyCupPlayoffs | 2,421,065 |
| 2014NBAPlayoffs | 500,170 |
| 2014KentuckyDerbyHorseRace | 233,172 |
| 2014BelmontStakesHorseRace | 226,160 |
| 2014FIFAWorldCupStagesA+B | 5,867,783 |
| TestingData | |
| 2013MLBWorldSeriesGame5 | 1,052,852 |
| 2013MLBWorldSeriesGame6 | 1,026,848 |
| 2013HonshuEarthquake | 444,018 |
| 2014NFLSuperBowl | 1,024,367 |
| 2014FIFAWorldCupThirdPlace | 809,426 |
| 2014FIFAWorldCupFinal | 1,166,767 |
| 2014IwakiEarthquake | 358,966 |
| Total | 16,305,443 | | 0 |
| Sport | KeyMoments |
| --- | --- |
| TrainingData | |
| 2010NFLDivisionChampionship | 13 | | | 2012PremierLeagueSoccerGames | 21 |
| --- | --- |
| 2014NHLStanleyCupPlayoffs | 24 |
| 2014NBAPlayoffs | 3 |
| 2014KentuckyDerbyHorseRace | 3 |
| 2014BelmontStakesHorseRace | 3 |
| 2014FIFAWorldCupStagesA+B | 80 |
| TestingData | |
| 2013MLBWorldSeriesGame5 | 7 |
| 2013MLBWorldSeriesGame6 | 8 |
| 2014NFLSuperBowl | 13 |
| 2014FIFAWorldCupThirdPlace | 11 |
| 2014FIFAWorldCupFinal | 7 |
| Total | 193 | | 1 |
| Sport | KeyMoments |
| --- | --- |
| TrainingData | |
| 2010NFLDivisionChampionship | 13 | | | 2013MLBWorldSeriesGame6 | 1,026,848 |
| --- | --- |
| 2013HonshuEarthquake | 444,018 |
| 2014NFLSuperBowl | 1,024,367 |
| 2014FIFAWorldCupThirdPlace | 809,426 |
| 2014FIFAWorldCupFinal | 1,166,767 |
| 2014IwakiEarthquake | 358,966 |
| Total | 16,305,443 | | 0 |
| | Gradual | Sharp | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P |
| BOR10001 | 11 | 11 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | - |
| BOR10002 | 11 | 9 | 0 | 2 | 1 | 0.818 | 0.9 | 0 | 0 | 0 | 0 | - |
| NAD57 | 25 | 22 | 1 | 3 | 0.957 | 0.88 | 0.917 | 45 | 45 | 4 | 0 | 0.918 | | | NAD58 | 44 | 37 | 0 | 7 | 1 | 0.841 | 0.914 | 40 | 33 | 0 | 7 | 1 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| anni001 | 8 | 6 | 0 | 2 | 1 | 0.75 | 0.857 | 0 | 0 | 1 | 0 | 0 |
| anni005 | 27 | 26 | 2 | 1 | 0.929 | 0.963 | 0.945 | 39 | 36 | 13 | 3 | 0.735 |
| anni006 | 31 | 27 | 3 | 4 | 0.9 | 0.871 | 0.885 | 42 | 41 | 0 | 1 | 1 |
| anni007 | 5 | 4 | 0 | 1 | 1 | 0.8 | 0.889 | 5 | 5 | 0 | 0 | 1 |
| anni008 | 13 | 12 | 0 | 1 | 1 | 0.923 | 0.96 | 2 | 2 | 0 | 0 | 1 |
| anni009 | 64 | 57 | 3 | 7 | 0.95 | 0.891 | 0.919 | 40 | 37 | 0 | 3 | 1 |
| anni010 | 56 | 50 | 11 | 6 | 0.82 | 0.893 | 0.855 | 98 | 84 | 1 | 14 | 0.988 |
| Total | 295 | 261 | 20 | 34 | 0.929 | 0.885 | 0.906 | 311 | 283 | 19 | 28 | 0.937 | | 1 |
| | Gradual | Sharp | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P |
| BOR10001 | 11 | 11 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | - |
| BOR10002 | 11 | 9 | 0 | 2 | 1 | 0.818 | 0.9 | 0 | 0 | 0 | 0 | - |
| NAD57 | 25 | 22 | 1 | 3 | 0.957 | 0.88 | 0.917 | 45 | 45 | 4 | 0 | 0.918 | | | | Gradual | Sharp | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P |
| BOR10001 | 11 | 11 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | - |
| BOR10002 | 11 | 10 | 0 | 1 | 1 | 0.909 | 0.952 | 0 | 0 | 0 | 0 | - |
| NAD57 | 25 | 21 | 2 | 4 | 0.913 | 0.84 | 0.875 | 45 | 45 | 1 | 0 | 0.978 |
| NAD58 | 44 | 39 | 0 | 5 | 1 | 0.886 | 0.94 | 40 | 35 | 0 | 5 | 1 |
| anni001 | 8 | 6 | 0 | 2 | 1 | 0.75 | 0.857 | 0 | 0 | 0 | 0 | - |
| anni005 | 27 | 27 | 1 | 0 | 0.964 | 1 | 0.982 | 39 | 35 | 5 | 4 | 0.875 |
| anni006 | 31 | 27 | 5 | 4 | 0.844 | 0.871 | 0.857 | 42 | 39 | 0 | 3 | 1 |
| anni007 | 5 | 5 | 0 | 0 | 1 | 1 | 1 | 5 | 5 | 0 | 0 | 1 |
| anni008 | 13 | 13 | 0 | 0 | 1 | 1 | 1 | 2 | 2 | 0 | 0 | 1 |
| anni009 | 64 | 60 | 2 | 4 | 0.968 | 0.938 | 0.952 | 40 | 36 | 0 | 4 | 1 |
| anni010 | 56 | 50 | 9 | 6 | 0.847 | 0.893 | 0.87 | 98 | 84 | 0 | 14 | 1 |
| Total | 295 | 269 | 19 | 26 | 0.934 | 0.912 | 0.923 | 311 | 281 | 6 | 30 | 0.979 | | 0 |
| | Gradual | Sharp | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P |
| BOR10001 | 11 | 11 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | - |
| BOR10002 | 11 | 9 | 0 | 2 | 1 | 0.818 | 0.9 | 0 | 0 | 0 | 0 | - |
| NAD57 | 25 | 22 | 1 | 3 | 0.957 | 0.88 | 0.917 | 45 | 45 | 4 | 0 | 0.918 |
| NAD58 | 44 | 37 | 0 | 7 | 1 | 0.841 | 0.914 | 40 | 33 | 0 | 7 | 1 |
| anni001 | 8 | 6 | 0 | 2 | 1 | 0.75 | 0.857 | 0 | 0 | 1 | 0 | 0 |
| anni005 | 27 | 26 | 2 | 1 | 0.929 | 0.963 | 0.945 | 39 | 36 | 13 | 3 | 0.735 |
| anni006 | 31 | 27 | 3 | 4 | 0.9 | 0.871 | 0.885 | 42 | 41 | 0 | 1 | 1 |
| anni007 | 5 | 4 | 0 | 1 | 1 | 0.8 | 0.889 | 5 | 5 | 0 | 0 | 1 |
| anni008 | 13 | 12 | 0 | 1 | 1 | 0.923 | 0.96 | 2 | 2 | 0 | 0 | 1 | | | anni009 | 64 | 57 | 3 | 7 | 0.95 | 0.891 | 0.919 | 40 | 37 | 0 | 3 | 1 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| anni010 | 56 | 50 | 11 | 6 | 0.82 | 0.893 | 0.855 | 98 | 84 | 1 | 14 | 0.988 |
| Total | 295 | 261 | 20 | 34 | 0.929 | 0.885 | 0.906 | 311 | 283 | 19 | 28 | 0.937 | | 1 |
| | Gradual | Sharp | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P |
| BOR10001 | 11 | 11 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | - |
| BOR10002 | 11 | 9 | 0 | 2 | 1 | 0.818 | 0.9 | 0 | 0 | 0 | 0 | - |
| NAD57 | 25 | 22 | 1 | 3 | 0.957 | 0.88 | 0.917 | 45 | 45 | 4 | 0 | 0.918 |
| NAD58 | 44 | 37 | 0 | 7 | 1 | 0.841 | 0.914 | 40 | 33 | 0 | 7 | 1 |
| anni001 | 8 | 6 | 0 | 2 | 1 | 0.75 | 0.857 | 0 | 0 | 1 | 0 | 0 |
| anni005 | 27 | 26 | 2 | 1 | 0.929 | 0.963 | 0.945 | 39 | 36 | 13 | 3 | 0.735 |
| anni006 | 31 | 27 | 3 | 4 | 0.9 | 0.871 | 0.885 | 42 | 41 | 0 | 1 | 1 |
| anni007 | 5 | 4 | 0 | 1 | 1 | 0.8 | 0.889 | 5 | 5 | 0 | 0 | 1 |
| anni008 | 13 | 12 | 0 | 1 | 1 | 0.923 | 0.96 | 2 | 2 | 0 | 0 | 1 | | | NAD57 | 25 | 21 | 2 | 4 | 0.913 | 0.84 | 0.875 | 45 | 45 | 1 | 0 | 0.978 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| NAD58 | 44 | 39 | 0 | 5 | 1 | 0.886 | 0.94 | 40 | 35 | 0 | 5 | 1 |
| anni001 | 8 | 6 | 0 | 2 | 1 | 0.75 | 0.857 | 0 | 0 | 0 | 0 | - |
| anni005 | 27 | 27 | 1 | 0 | 0.964 | 1 | 0.982 | 39 | 35 | 5 | 4 | 0.875 |
| anni006 | 31 | 27 | 5 | 4 | 0.844 | 0.871 | 0.857 | 42 | 39 | 0 | 3 | 1 |
| anni007 | 5 | 5 | 0 | 0 | 1 | 1 | 1 | 5 | 5 | 0 | 0 | 1 |
| anni008 | 13 | 13 | 0 | 0 | 1 | 1 | 1 | 2 | 2 | 0 | 0 | 1 |
| anni009 | 64 | 60 | 2 | 4 | 0.968 | 0.938 | 0.952 | 40 | 36 | 0 | 4 | 1 |
| anni010 | 56 | 50 | 9 | 6 | 0.847 | 0.893 | 0.87 | 98 | 84 | 0 | 14 | 1 |
| Total | 295 | 269 | 19 | 26 | 0.934 | 0.912 | 0.923 | 311 | 281 | 6 | 30 | 0.979 | | 0 |
| Expertise | Melody | Structure | Preference |
| --- | --- | --- | --- |
| low | .598 | .545 | .542 |
| middle | .719 | .692 | .619 |
| high | .687 | .712 | .712 |
| all | .691 | .684 | .654 |
| low | .583 | .458 | .583 |
| middle | .570 | .427 | .567 | | | high | .598 | .511 | .565 |
| --- | --- | --- | --- |
| all | .577 | .447 | .567 | | 1 |
| Expertise | Melody | Structure | Preference |
| --- | --- | --- | --- |
| low | .598 | .545 | .542 |
| middle | .719 | .692 | .619 |
| high | .687 | .712 | .712 |
| all | .691 | .684 | .654 |
| low | .583 | .458 | .583 |
| middle | .570 | .427 | .567 | | | | MusicalEnsembleGroup | NoMusicalEnsembleGroup | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | Human-like | Harmony | Melody | Human-like | Harmony | Melody |
| OdetoJoy<br>-Layered<br>HMM | 3.125 | 3.250 | 3.125 | 3.8 | 4.0 | 3.8 |
| WeThree<br>Kings-<br>Layered<br>HMM | 3.500 | 3.125 | 3.125 | 2.4 | 1.8 | 2.2 |
| Pachelbel’s<br>Canon-<br>TVAR(11) | 3.438 | 3.375 | 3.063 | 3.5 | 3.6 | 3.2 | | 0 |
| Expertise | Melody | Structure | Preference |
| --- | --- | --- | --- |
| low | .598 | .545 | .542 |
| middle | .719 | .692 | .619 |
| high | .687 | .712 | .712 |
| all | .691 | .684 | .654 |
| low | .583 | .458 | .583 | | | middle | .570 | .427 | .567 |
| --- | --- | --- | --- |
| high | .598 | .511 | .565 |
| all | .577 | .447 | .567 | | 1 |
| Expertise | Melody | Structure | Preference |
| --- | --- | --- | --- |
| low | .598 | .545 | .542 |
| middle | .719 | .692 | .619 |
| high | .687 | .712 | .712 |
| all | .691 | .684 | .654 |
| low | .583 | .458 | .583 | | | WeThree<br>Kings-<br>Layered<br>HMM | 3.500 | 3.125 | 3.125 | 2.4 | 1.8 | 2.2 |
| --- | --- | --- | --- | --- | --- | --- |
| Pachelbel’s<br>Canon-<br>TVAR(11) | 3.438 | 3.375 | 3.063 | 3.5 | 3.6 | 3.2 | | 0 |
| Graph | TSM-MWC<br>w | LSCC<br>w(w)maxavg | RRWL<br>w(w)maxavg | TRSC<br>w(w)maxavg |
| --- | --- | --- | --- | --- |
| frb56-25-1<br>frb56-25-2<br>frb56-25-3<br>frb56-25-4<br>frb56-25-5<br>frb59-26-1<br>frb59-26-2<br>frb59-26-3<br>frb59-26-4<br>frb59-26-5 | 3693<br>4470<br>3958<br>4609<br>4023<br>4469<br>5105<br>4373<br>4916<br>5038 | 5886(5834.58)<br>5886(5826.08)<br>5844(5792.07)<br>5873(5833.78)<br>5817(5766.64)<br>6591(6548.68)<br>6645(6558.62)<br>6576(6523.49)<br>6592(6501.58)<br>6584(6527.69) | 5916(5841.13)<br>5886(5827.72)<br>5842(5795.35)<br>5877(5830.09)<br>5810(5774.23)<br>6591(6539.59)<br>6645(6552.96)<br>6606(6532.8)<br>6592(6505.26)<br>6569(6523.45) | 5916(5850.63)<br>5882(5842.6)<br>5854(5805.8)<br>5877(5840.62)<br>5843(5785.52)<br>6591(6554.16)<br>6645(6568.67)<br>6606(6542.24)<br>6592(6518.74)<br>6581(6533.69) |
| frb65-28-1<br>frb65-28-2<br>frb65-28-3<br>frb65-28-4<br>frb65-28-5<br>frb70-30-1<br>frb70-30-2<br>frb70-30-3<br>frb70-30-4<br>frb70-30-5<br>frb75-32-1<br>frb75-32-2<br>frb75-32-3<br>frb75-32-4<br>frb75-32-5<br>frb80-33-1<br>frb80-33-2<br>frb80-33-3<br>frb80-33-4<br>frb80-33-5 | 5208<br>4788<br>4857<br>4587<br>4881<br>5125<br>5159<br>4635<br>4918<br>5402<br>5168<br>5820<br>5928<br>6315<br>5393<br>5819<br>5783<br>5954<br>6655<br>6167 | 7410(7319.63)<br>7421(7369.89)<br>7449(7359.52)<br>7433(7366.07)<br>7451(7354.89)<br>7717(7597.72)<br>7749(7668.98)<br>7678(7622.72)<br>7739(7680.75)<br>7749(7669.0)<br>8615(8537.8)<br>8644(8569.07)<br>8619(8506.95)<br>8714(8589.85)<br>8663(8590.24)<br>9353(9249.81)<br>9343(9251.12)<br>7449(7359.52)<br>9387(9305.08)<br>9413(9337.37) | 7405(7353.08)<br>7425(7365.99)<br>7434(7361.07)<br>7438(7366.83)<br>7451(7354.73)<br>7688(7600.97)<br>7734(7667.96)<br>7733(7620.69)<br>7750(7684.43)<br>7725(7666.93)<br>8637(8532.98)<br>8657(8570.63)<br>8565(8496.14)<br>8688(8590.29)<br>8655(8591.12)<br>9461(9242.11)<br>9390(9248.75)<br>7434(7361.07)<br>9430(9301.91)<br>9415(9341.21) | 7432(7377.73)<br>7441(7380.56)<br>7445(7377.62)<br>7448(7381.88)<br>7451(7374.99)<br>7772(7617.76)<br>7777(7689.7)<br>7696(7638.95)<br>7766(7703.22)<br>7740(7683.99)<br>8621(8556.81)<br>8667(8583.37)<br>8600(8528.81)<br>8692(8607.74)<br>8644(8602.52)<br>9407(9294.27)<br>9387(9293.51)<br>7445(7377.62)<br>9408(9332.44)<br>9478(9360.45) |
| C2000.9<br>C4000.5 | 8338<br>2438 | 10999(10942.27)<br>2792(2792.0) | 10999(10951.67)<br>2792(2792.0) | 10999(10965.43)<br>2792(2792.0) | | | hamming10-4 | 4828 | 5129(5129.0) | 5129(5129.0) | 5129(5129.0) |
| --- | --- | --- | --- | --- |
| keller6 | 4793 | 8062(7841.39) | 8062(7891.05) | 8062(7961.9) |
| MANNa45<br>MANNa81 | ∗<br>34265<br>110037 | 34254(34244.51)<br>111126(111093.81) | 34263(34254.75)<br>111346(111306.32) | 34262(34254.18)<br>111356(111305.79) | | 1 |
| Graph | TSM-MWC<br>w | LSCC<br>w(w)maxavg | RRWL<br>w(w)maxavg | TRSC<br>w(w)maxavg |
| --- | --- | --- | --- | --- |
| frb56-25-1<br>frb56-25-2<br>frb56-25-3<br>frb56-25-4<br>frb56-25-5<br>frb59-26-1<br>frb59-26-2<br>frb59-26-3<br>frb59-26-4<br>frb59-26-5 | 3693<br>4470<br>3958<br>4609<br>4023<br>4469<br>5105<br>4373<br>4916<br>5038 | 5886(5834.58)<br>5886(5826.08)<br>5844(5792.07)<br>5873(5833.78)<br>5817(5766.64)<br>6591(6548.68)<br>6645(6558.62)<br>6576(6523.49)<br>6592(6501.58)<br>6584(6527.69) | 5916(5841.13)<br>5886(5827.72)<br>5842(5795.35)<br>5877(5830.09)<br>5810(5774.23)<br>6591(6539.59)<br>6645(6552.96)<br>6606(6532.8)<br>6592(6505.26)<br>6569(6523.45) | 5916(5850.63)<br>5882(5842.6)<br>5854(5805.8)<br>5877(5840.62)<br>5843(5785.52)<br>6591(6554.16)<br>6645(6568.67)<br>6606(6542.24)<br>6592(6518.74)<br>6581(6533.69) |
| frb65-28-1<br>frb65-28-2<br>frb65-28-3<br>frb65-28-4<br>frb65-28-5<br>frb70-30-1<br>frb70-30-2<br>frb70-30-3<br>frb70-30-4<br>frb70-30-5<br>frb75-32-1<br>frb75-32-2<br>frb75-32-3<br>frb75-32-4<br>frb75-32-5<br>frb80-33-1<br>frb80-33-2<br>frb80-33-3<br>frb80-33-4<br>frb80-33-5 | 5208<br>4788<br>4857<br>4587<br>4881<br>5125<br>5159<br>4635<br>4918<br>5402<br>5168<br>5820<br>5928<br>6315<br>5393<br>5819<br>5783<br>5954<br>6655<br>6167 | 7410(7319.63)<br>7421(7369.89)<br>7449(7359.52)<br>7433(7366.07)<br>7451(7354.89)<br>7717(7597.72)<br>7749(7668.98)<br>7678(7622.72)<br>7739(7680.75)<br>7749(7669.0)<br>8615(8537.8)<br>8644(8569.07)<br>8619(8506.95)<br>8714(8589.85)<br>8663(8590.24)<br>9353(9249.81)<br>9343(9251.12)<br>7449(7359.52)<br>9387(9305.08)<br>9413(9337.37) | 7405(7353.08)<br>7425(7365.99)<br>7434(7361.07)<br>7438(7366.83)<br>7451(7354.73)<br>7688(7600.97)<br>7734(7667.96)<br>7733(7620.69)<br>7750(7684.43)<br>7725(7666.93)<br>8637(8532.98)<br>8657(8570.63)<br>8565(8496.14)<br>8688(8590.29)<br>8655(8591.12)<br>9461(9242.11)<br>9390(9248.75)<br>7434(7361.07)<br>9430(9301.91)<br>9415(9341.21) | 7432(7377.73)<br>7441(7380.56)<br>7445(7377.62)<br>7448(7381.88)<br>7451(7374.99)<br>7772(7617.76)<br>7777(7689.7)<br>7696(7638.95)<br>7766(7703.22)<br>7740(7683.99)<br>8621(8556.81)<br>8667(8583.37)<br>8600(8528.81)<br>8692(8607.74)<br>8644(8602.52)<br>9407(9294.27)<br>9387(9293.51)<br>7445(7377.62)<br>9408(9332.44)<br>9478(9360.45) |
| C2000.9<br>C4000.5 | 8338<br>2438 | 10999(10942.27)<br>2792(2792.0) | 10999(10951.67)<br>2792(2792.0) | 10999(10965.43)<br>2792(2792.0) | | | | | | | | |
| --- | --- | --- | --- | --- | --- |
| 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>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<br>72,5M<br>602582<br>20192 | 108,1<br>78,1M<br>642665<br>28766 |
| geo50-20-d4-75-2 | t<br>c<br>r<br>n | 226,1<br>191,8M<br>778758<br>20069 | 401,8<br>310,3M<br>1,3M<br>60182 | 34,8<br>28,2M<br>117241<br>3735 | 39,5<br>28,8M<br>124163<br>5484 | | 0 |
| Graph | TSM-MWC<br>w | LSCC<br>w(w)maxavg | RRWL<br>w(w)maxavg | TRSC<br>w(w)maxavg |
| --- | --- | --- | --- | --- |
| frb56-25-1<br>frb56-25-2<br>frb56-25-3<br>frb56-25-4<br>frb56-25-5<br>frb59-26-1<br>frb59-26-2<br>frb59-26-3<br>frb59-26-4<br>frb59-26-5 | 3693<br>4470<br>3958<br>4609<br>4023<br>4469<br>5105<br>4373<br>4916<br>5038 | 5886(5834.58)<br>5886(5826.08)<br>5844(5792.07)<br>5873(5833.78)<br>5817(5766.64)<br>6591(6548.68)<br>6645(6558.62)<br>6576(6523.49)<br>6592(6501.58)<br>6584(6527.69) | 5916(5841.13)<br>5886(5827.72)<br>5842(5795.35)<br>5877(5830.09)<br>5810(5774.23)<br>6591(6539.59)<br>6645(6552.96)<br>6606(6532.8)<br>6592(6505.26)<br>6569(6523.45) | 5916(5850.63)<br>5882(5842.6)<br>5854(5805.8)<br>5877(5840.62)<br>5843(5785.52)<br>6591(6554.16)<br>6645(6568.67)<br>6606(6542.24)<br>6592(6518.74)<br>6581(6533.69) |
| frb65-28-1<br>frb65-28-2<br>frb65-28-3<br>frb65-28-4<br>frb65-28-5<br>frb70-30-1<br>frb70-30-2<br>frb70-30-3<br>frb70-30-4<br>frb70-30-5<br>frb75-32-1<br>frb75-32-2<br>frb75-32-3<br>frb75-32-4<br>frb75-32-5<br>frb80-33-1<br>frb80-33-2<br>frb80-33-3<br>frb80-33-4<br>frb80-33-5 | 5208<br>4788<br>4857<br>4587<br>4881<br>5125<br>5159<br>4635<br>4918<br>5402<br>5168<br>5820<br>5928<br>6315<br>5393<br>5819<br>5783<br>5954<br>6655<br>6167 | 7410(7319.63)<br>7421(7369.89)<br>7449(7359.52)<br>7433(7366.07)<br>7451(7354.89)<br>7717(7597.72)<br>7749(7668.98)<br>7678(7622.72)<br>7739(7680.75)<br>7749(7669.0)<br>8615(8537.8)<br>8644(8569.07)<br>8619(8506.95)<br>8714(8589.85)<br>8663(8590.24)<br>9353(9249.81)<br>9343(9251.12)<br>7449(7359.52)<br>9387(9305.08)<br>9413(9337.37) | 7405(7353.08)<br>7425(7365.99)<br>7434(7361.07)<br>7438(7366.83)<br>7451(7354.73)<br>7688(7600.97)<br>7734(7667.96)<br>7733(7620.69)<br>7750(7684.43)<br>7725(7666.93)<br>8637(8532.98)<br>8657(8570.63)<br>8565(8496.14)<br>8688(8590.29)<br>8655(8591.12)<br>9461(9242.11)<br>9390(9248.75)<br>7434(7361.07)<br>9430(9301.91)<br>9415(9341.21) | 7432(7377.73)<br>7441(7380.56)<br>7445(7377.62)<br>7448(7381.88)<br>7451(7374.99)<br>7772(7617.76)<br>7777(7689.7)<br>7696(7638.95)<br>7766(7703.22)<br>7740(7683.99)<br>8621(8556.81)<br>8667(8583.37)<br>8600(8528.81)<br>8692(8607.74)<br>8644(8602.52)<br>9407(9294.27)<br>9387(9293.51)<br>7445(7377.62)<br>9408(9332.44)<br>9478(9360.45) |
| C2000.9<br>C4000.5 | 8338<br>2438 | 10999(10942.27)<br>2792(2792.0) | 10999(10951.67)<br>2792(2792.0) | 10999(10965.43)<br>2792(2792.0) |
| hamming10-4 | 4828 | 5129(5129.0) | 5129(5129.0) | 5129(5129.0) | | | keller6 | 4793 | 8062(7841.39) | 8062(7891.05) | 8062(7961.9) |
| --- | --- | --- | --- | --- |
| MANNa45<br>MANNa81 | ∗<br>34265<br>110037 | 34254(34244.51)<br>111126(111093.81) | 34263(34254.75)<br>111346(111306.32) | 34262(34254.18)<br>111356(111305.79) | | 1 |
| Graph | TSM-MWC<br>w | LSCC<br>w(w)maxavg | RRWL<br>w(w)maxavg | TRSC<br>w(w)maxavg |
| --- | --- | --- | --- | --- |
| frb56-25-1<br>frb56-25-2<br>frb56-25-3<br>frb56-25-4<br>frb56-25-5<br>frb59-26-1<br>frb59-26-2<br>frb59-26-3<br>frb59-26-4<br>frb59-26-5 | 3693<br>4470<br>3958<br>4609<br>4023<br>4469<br>5105<br>4373<br>4916<br>5038 | 5886(5834.58)<br>5886(5826.08)<br>5844(5792.07)<br>5873(5833.78)<br>5817(5766.64)<br>6591(6548.68)<br>6645(6558.62)<br>6576(6523.49)<br>6592(6501.58)<br>6584(6527.69) | 5916(5841.13)<br>5886(5827.72)<br>5842(5795.35)<br>5877(5830.09)<br>5810(5774.23)<br>6591(6539.59)<br>6645(6552.96)<br>6606(6532.8)<br>6592(6505.26)<br>6569(6523.45) | 5916(5850.63)<br>5882(5842.6)<br>5854(5805.8)<br>5877(5840.62)<br>5843(5785.52)<br>6591(6554.16)<br>6645(6568.67)<br>6606(6542.24)<br>6592(6518.74)<br>6581(6533.69) |
| frb65-28-1<br>frb65-28-2<br>frb65-28-3<br>frb65-28-4<br>frb65-28-5<br>frb70-30-1<br>frb70-30-2<br>frb70-30-3<br>frb70-30-4<br>frb70-30-5<br>frb75-32-1<br>frb75-32-2<br>frb75-32-3<br>frb75-32-4<br>frb75-32-5<br>frb80-33-1<br>frb80-33-2<br>frb80-33-3<br>frb80-33-4<br>frb80-33-5 | 5208<br>4788<br>4857<br>4587<br>4881<br>5125<br>5159<br>4635<br>4918<br>5402<br>5168<br>5820<br>5928<br>6315<br>5393<br>5819<br>5783<br>5954<br>6655<br>6167 | 7410(7319.63)<br>7421(7369.89)<br>7449(7359.52)<br>7433(7366.07)<br>7451(7354.89)<br>7717(7597.72)<br>7749(7668.98)<br>7678(7622.72)<br>7739(7680.75)<br>7749(7669.0)<br>8615(8537.8)<br>8644(8569.07)<br>8619(8506.95)<br>8714(8589.85)<br>8663(8590.24)<br>9353(9249.81)<br>9343(9251.12)<br>7449(7359.52)<br>9387(9305.08)<br>9413(9337.37) | 7405(7353.08)<br>7425(7365.99)<br>7434(7361.07)<br>7438(7366.83)<br>7451(7354.73)<br>7688(7600.97)<br>7734(7667.96)<br>7733(7620.69)<br>7750(7684.43)<br>7725(7666.93)<br>8637(8532.98)<br>8657(8570.63)<br>8565(8496.14)<br>8688(8590.29)<br>8655(8591.12)<br>9461(9242.11)<br>9390(9248.75)<br>7434(7361.07)<br>9430(9301.91)<br>9415(9341.21) | 7432(7377.73)<br>7441(7380.56)<br>7445(7377.62)<br>7448(7381.88)<br>7451(7374.99)<br>7772(7617.76)<br>7777(7689.7)<br>7696(7638.95)<br>7766(7703.22)<br>7740(7683.99)<br>8621(8556.81)<br>8667(8583.37)<br>8600(8528.81)<br>8692(8607.74)<br>8644(8602.52)<br>9407(9294.27)<br>9387(9293.51)<br>7445(7377.62)<br>9408(9332.44)<br>9478(9360.45) |
| C2000.9<br>C4000.5 | 8338<br>2438 | 10999(10942.27)<br>2792(2792.0) | 10999(10951.67)<br>2792(2792.0) | 10999(10965.43)<br>2792(2792.0) |
| hamming10-4 | 4828 | 5129(5129.0) | 5129(5129.0) | 5129(5129.0) | | | 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<br>72,5M<br>602582<br>20192 | 108,1<br>78,1M<br>642665<br>28766 |
| geo50-20-d4-75-2 | t<br>c<br>r<br>n | 226,1<br>191,8M<br>778758<br>20069 | 401,8<br>310,3M<br>1,3M<br>60182 | 34,8<br>28,2M<br>117241<br>3735 | 39,5<br>28,8M<br>124163<br>5484 | | 0 |
| CountOnce | MultiCount | |
| --- | --- | --- |
| TimetoRecall | FP-90FP-95FP-99 | FP-90FP-95FP-99 |
| 30 | 1.73T1.36T0.44T<br>1.36T0.9T0.23T<br>1.08T0.65T0.15T<br>0.88T0.5T0.11T<br>0.72T0.4T0.08T<br>0.62T0.34T0.07T | 10T5T0.99T<br>4.69T2.34T0.46T<br>3.06T1.52T0.3T<br>2.31T1.15T0.23T<br>1.89T0.94T0.18T<br>1.43T0.71T0.14T |
| 60 | | |
| 90 | | |
| 120 | | | | | 150 |
| --- |
| 180 | | 1 |
| CountOnce | MultiCount | |
| --- | --- | --- |
| TimetoRecall | FP-90FP-95FP-99 | FP-90FP-95FP-99 |
| 30 | 1.73T1.36T0.44T<br>1.36T0.9T0.23T<br>1.08T0.65T0.15T<br>0.88T0.5T0.11T<br>0.72T0.4T0.08T<br>0.62T0.34T0.07T | 10T5T0.99T<br>4.69T2.34T0.46T<br>3.06T1.52T0.3T<br>2.31T1.15T0.23T<br>1.89T0.94T0.18T<br>1.43T0.71T0.14T |
| 60 | | |
| 90 | | |
| 120 | | | | | #Params | RVD | |
| --- | --- | --- |
| @1 | @10 | |
| 0.09m<br>1.82m | 0.106<br>0.190 | 0.316<br>0.452 |
| 10.2m<br>10.6m<br>10.4m<br>10.8m | 0.175<br>0.187<br>0.286<br>0.293 | 0.465<br>0.492<br>0.573<br>0.581 |
| 11.1m<br>11.7m | 0.307<br>0.308 | 0.600<br>0.608 | | 0 |
| CountOnce | MultiCount | |
| --- | --- | --- |
| TimetoRecall | FP-90FP-95FP-99 | FP-90FP-95FP-99 |
| 30 | 1.73T1.36T0.44T<br>1.36T0.9T0.23T<br>1.08T0.65T0.15T<br>0.88T0.5T0.11T<br>0.72T0.4T0.08T<br>0.62T0.34T0.07T | 10T5T0.99T<br>4.69T2.34T0.46T<br>3.06T1.52T0.3T<br>2.31T1.15T0.23T<br>1.89T0.94T0.18T<br>1.43T0.71T0.14T |
| 60 | | |
| 90 | | | | | 120 |
| --- |
| 150 |
| 180 | | 1 |
| CountOnce | MultiCount | |
| --- | --- | --- |
| TimetoRecall | FP-90FP-95FP-99 | FP-90FP-95FP-99 |
| 30 | 1.73T1.36T0.44T<br>1.36T0.9T0.23T<br>1.08T0.65T0.15T<br>0.88T0.5T0.11T<br>0.72T0.4T0.08T<br>0.62T0.34T0.07T | 10T5T0.99T<br>4.69T2.34T0.46T<br>3.06T1.52T0.3T<br>2.31T1.15T0.23T<br>1.89T0.94T0.18T<br>1.43T0.71T0.14T |
| 60 | | |
| 90 | | | | | 0.09m<br>1.82m | 0.106<br>0.190 | 0.316<br>0.452 |
| --- | --- | --- |
| 10.2m<br>10.6m<br>10.4m<br>10.8m | 0.175<br>0.187<br>0.286<br>0.293 | 0.465<br>0.492<br>0.573<br>0.581 |
| 11.1m<br>11.7m | 0.307<br>0.308 | 0.600<br>0.608 | | 0 |
| | Scale176×144 | Scale192×160 | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | MOS | PSNR | SSIM | MOS | PSNR | SSIM |
| SGEN | 24.12 | 0.7202 | 4.6333 | 24.55 | 0.733 | 4.6000 | 24.92 | 0.7429 | | | SGEN-MSE | 24.61 | 0.7501 | 4.3667 | 24.98 | 0.7576 | 4.6333 | 25.39 | 0.7686 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MEN | 23.50 | 0.6942 | 1.9833 | 23.97 | 0.7052 | 2.1167 | 24.46 | 0.7197 |
| AEN | 24.14 | 0.7274 | 3.2333 | 24.62 | 0.7411 | 3.3000 | 24.97 | 0.7533 |
| CEN | 24.42 | 0.7397 | 4.1000 | 24.82 | 0.7545 | 4.0500 | 25.20 | 0.7646 | | 1 |
| | Scale176×144 | Scale192×160 | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | MOS | PSNR | SSIM | MOS | PSNR | SSIM |
| SGEN | 24.12 | 0.7202 | 4.6333 | 24.55 | 0.733 | 4.6000 | 24.92 | 0.7429 | | | | Scale128×96 | Scale144×112 | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | MOS | PSNR | SSIM | MOS | PSNR | SSIM |
| SGEN | 22.37 | 0.6555 | 4.4833 | 23.08 | 0.6863 | 4.7833 | 23.61 | 0.7006 |
| SGEN-MSE | 23.00 | 0.6989 | 4.3667 | 23.60 | 0.7161 | 4.5000 | 24.12 | 0.7327 |
| SRCNN | 21.72 | 0.5923 | 1.0000 | 22.22 | 0.6094 | 1.0667 | 22.69 | 0.6236 |
| SRResNet | 22.73 | 0.6827 | 3.0333 | 23.29 | 0.7016 | 3.0667 | 23.81 | 0.7166 |
| SRGAN | 22.29 | 0.6486 | 2.9444 | 22.78 | 0.6796 | 3.0000 | 23.43 | 0.6927 |
| RED-Net | 22.77 | 0.6809 | 3.6667 | 23.32 | 0.7001 | 3.6333 | 23.83 | 0.7147 |
| URDGN | 22.54 | 0.6688 | 2.8667 | 23.10 | 0.6885 | 3.0667 | 23.56 | 0.7044 | | 0 |
| | Scale176×144 | Scale192×160 | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | MOS | PSNR | SSIM | MOS | PSNR | SSIM |
| SGEN | 24.12 | 0.7202 | 4.6333 | 24.55 | 0.733 | 4.6000 | 24.92 | 0.7429 | | | SGEN-MSE | 24.61 | 0.7501 | 4.3667 | 24.98 | 0.7576 | 4.6333 | 25.39 | 0.7686 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MEN | 23.50 | 0.6942 | 1.9833 | 23.97 | 0.7052 | 2.1167 | 24.46 | 0.7197 |
| AEN | 24.14 | 0.7274 | 3.2333 | 24.62 | 0.7411 | 3.3000 | 24.97 | 0.7533 |
| CEN | 24.42 | 0.7397 | 4.1000 | 24.82 | 0.7545 | 4.0500 | 25.20 | 0.7646 | | 1 |
| | Scale176×144 | Scale192×160 | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | MOS | PSNR | SSIM | MOS | PSNR | SSIM |
| SGEN | 24.12 | 0.7202 | 4.6333 | 24.55 | 0.733 | 4.6000 | 24.92 | 0.7429 | | | SGEN | 22.37 | 0.6555 | 4.4833 | 23.08 | 0.6863 | 4.7833 | 23.61 | 0.7006 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| SGEN-MSE | 23.00 | 0.6989 | 4.3667 | 23.60 | 0.7161 | 4.5000 | 24.12 | 0.7327 |
| SRCNN | 21.72 | 0.5923 | 1.0000 | 22.22 | 0.6094 | 1.0667 | 22.69 | 0.6236 |
| SRResNet | 22.73 | 0.6827 | 3.0333 | 23.29 | 0.7016 | 3.0667 | 23.81 | 0.7166 |
| SRGAN | 22.29 | 0.6486 | 2.9444 | 22.78 | 0.6796 | 3.0000 | 23.43 | 0.6927 |
| RED-Net | 22.77 | 0.6809 | 3.6667 | 23.32 | 0.7001 | 3.6333 | 23.83 | 0.7147 |
| URDGN | 22.54 | 0.6688 | 2.8667 | 23.10 | 0.6885 | 3.0667 | 23.56 | 0.7044 | | 0 |
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