premise
string
hypothesis
string
label
int64
| | RunningTime(seconds) | Precision | Recall | F-measure | | --- | --- | --- | --- | --- | | P-CENI | 5877 | 0.083 | 0.557 | 0.145 |
| C-CENI | 5415 | 0.082 | 0.539 | 0.142 | | --- | --- | --- | --- | --- | | I-CENI | 7358 | 0.078 | 0.571 | 0.137 | | MMRate | 21677 | 0.085 | 0.565 | 0.148 | | NetRate | 14404 | 0.081 | 0.566 | 0.142 |
1
| | RunningTime(seconds) | Precision | Recall | F-measure | | --- | --- | --- | --- | --- | | P-CENI | 5877 | 0.083 | 0.557 | 0.145 |
| | RunningTime(seconds) | Precision | Recall | F-measure | | --- | --- | --- | --- | --- | | P-CENI | 8182 | 0.058 | 0.140 | 0.082 | | C-CENI | 7729 | 0.038 | 0.128 | 0.059 | | I-CENI | 8559 | 0.043 | 0.233 | 0.073 | | MMRate | 37328 | 0.046 | 0.144 | 0.070 | | NetRate | 16461 | 0.045 | 0.168 | 0.071 |
0
| | RunningTime(seconds) | Precision | Recall | F-measure | | --- | --- | --- | --- | --- | | P-CENI | 5877 | 0.083 | 0.557 | 0.145 | | C-CENI | 5415 | 0.082 | 0.539 | 0.142 |
| I-CENI | 7358 | 0.078 | 0.571 | 0.137 | | --- | --- | --- | --- | --- | | MMRate | 21677 | 0.085 | 0.565 | 0.148 | | NetRate | 14404 | 0.081 | 0.566 | 0.142 |
1
| | RunningTime(seconds) | Precision | Recall | F-measure | | --- | --- | --- | --- | --- | | P-CENI | 5877 | 0.083 | 0.557 | 0.145 | | C-CENI | 5415 | 0.082 | 0.539 | 0.142 |
| MMRate | 37328 | 0.046 | 0.144 | 0.070 | | --- | --- | --- | --- | --- | | NetRate | 16461 | 0.045 | 0.168 | 0.071 |
0
| Method | G1 | G2 | G3 | G4 | Total | | --- | --- | --- | --- | --- | --- | | ML-CNN | 81.97 | 79.11 | 63.16 | 62.45 | 76.25 | | CF | 81.00 | 82.08 | 77.63 | 78.50 | 80.48 | | CRF | 85.00 | 84.33 | 81.25 | 82.50 | 83.95 | | G-tasks | 90.10 | 92.29 | 89.80 | 73.52 | 89.18 |
| S-CNN | 90.50 | 92.90 | 87.00 | 89.57 | 90.43 | | --- | --- | --- | --- | --- | --- | | M-CNN | 91.72 | 94.26 | 87.96 | 91.51 | 91.70 | | MG-CNN | 93.12 | 95.37 | 88.65 | 91.93 | 92.82 |
1
| Method | G1 | G2 | G3 | G4 | Total | | --- | --- | --- | --- | --- | --- | | ML-CNN | 81.97 | 79.11 | 63.16 | 62.45 | 76.25 | | CF | 81.00 | 82.08 | 77.63 | 78.50 | 80.48 | | CRF | 85.00 | 84.33 | 81.25 | 82.50 | 83.95 | | G-tasks | 90.10 | 92.29 | 89.80 | 73.52 | 89.18 |
| Method | G1 | G2 | G3 | G4 | Total | | --- | --- | --- | --- | --- | --- | | S-extract | 81.84 | 82.07 | 67.51 | 69.25 | 78.31 | | M-extract | 84.98 | 89.89 | 81.41 | 81.03 | 85.29 | | S-CNN | 90.50 | 92.90 | 87.00 | 89.57 | 90.43 | | M-CNN | 91.72 | 94.26 | 87.96 | 91.51 | 91.70 | | MG-CNN | 93.12 | 95.37 | 88.65 | ...
0
| Method | G1 | G2 | G3 | G4 | Total | | --- | --- | --- | --- | --- | --- | | ML-CNN | 81.97 | 79.11 | 63.16 | 62.45 | 76.25 |
| CF | 81.00 | 82.08 | 77.63 | 78.50 | 80.48 | | --- | --- | --- | --- | --- | --- | | CRF | 85.00 | 84.33 | 81.25 | 82.50 | 83.95 | | G-tasks | 90.10 | 92.29 | 89.80 | 73.52 | 89.18 | | S-CNN | 90.50 | 92.90 | 87.00 | 89.57 | 90.43 | | M-CNN | 91.72 | 94.26 | 87.96 | 91.51 | 91.70 | | MG-CNN | 93.12 | 95.37 | 88.65 | ...
1
| Method | G1 | G2 | G3 | G4 | Total | | --- | --- | --- | --- | --- | --- | | ML-CNN | 81.97 | 79.11 | 63.16 | 62.45 | 76.25 |
| M-extract | 84.98 | 89.89 | 81.41 | 81.03 | 85.29 | | --- | --- | --- | --- | --- | --- | | S-CNN | 90.50 | 92.90 | 87.00 | 89.57 | 90.43 | | M-CNN | 91.72 | 94.26 | 87.96 | 91.51 | 91.70 | | MG-CNN | 93.12 | 95.37 | 88.65 | 91.93 | 92.82 | | CF | 81.00 | 82.08 | 77.63 | 78.50 | 80.48 | | CRF | 85.00 | 84.33 | 81.25 ...
0
| Surfaceexpression | Example | Weight | | --- | --- | --- | | Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | (Johnni(to))shita(done). | 16 | | Nounga(subject)/mo/da/nara | Johnga(subject)shita(do). | 15 |
| Nounwo(object)/ni/,/. | Johnni(object)shita(do). | 14 | | --- | --- | --- | | Nounhe(to)/de(in)/kara(from) | gakkou(school)he(to)iku(go). | 13 |
1
| Surfaceexpression | Example | Weight | | --- | --- | --- | | Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | (Johnni(to))shita(done). | 16 | | Nounga(subject)/mo/da/nara | Johnga(subject)shita(do). | 15 |
| Surfaceexpression(Notincluding“wa”) | Example | Weight | | --- | --- | --- | | Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | [Johnni(to)]shita(done). | 16 | | Nounga(subject)/mo/da/nara/koso | Johnga(subject)shita(done). | 15 | | Nounwo(object)/ni/,/. | Johnni(object)shita(done). | 14 | | Nounhe(to)/de(in)/kara(...
0
| Surfaceexpression | Example | Weight | | --- | --- | --- | | Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | (Johnni(to))shita(done). | 16 |
| Nounga(subject)/mo/da/nara | Johnga(subject)shita(do). | 15 | | --- | --- | --- | | Nounwo(object)/ni/,/. | Johnni(object)shita(do). | 14 | | Nounhe(to)/de(in)/kara(from) | gakkou(school)he(to)iku(go). | 13 |
1
| Surfaceexpression | Example | Weight | | --- | --- | --- | | Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | (Johnni(to))shita(done). | 16 |
| Nounwo(object)/ni/,/. | Johnni(object)shita(done). | 14 | | --- | --- | --- | | Nounhe(to)/de(in)/kara(from)/yori | gakkou(school)he(to)iku(go). | 13 |
0
| Models | IOU | Params | GFLOPs | | --- | --- | --- | --- | | ERFNet | 70.45 | 2038448 | 27.705 | | D* | 68.55 | 547120 | 10.597 | | DG2* | 65.35 | 395568 | 8.852 | | DG4* | 61.42 | 319792 | 7.980 | | DG8* | 59.15 | 281904 | 7.543 | | DG2S* | 65.36 | 395568 | 8.852 |
| DG4S* | 61.27 | 319792 | 7.980 | | --- | --- | --- | --- | | DG8S* | 59.89 | 281904 | 7.543 |
1
| Models | IOU | Params | GFLOPs | | --- | --- | --- | --- | | ERFNet | 70.45 | 2038448 | 27.705 | | D* | 68.55 | 547120 | 10.597 | | DG2* | 65.35 | 395568 | 8.852 | | DG4* | 61.42 | 319792 | 7.980 | | DG8* | 59.15 | 281904 | 7.543 | | DG2S* | 65.36 | 395568 | 8.852 |
| Models | IOU | Params | GFlops | | --- | --- | --- | --- | | D | 69.26 | 1291648 | 19.025 | | DG2 | 69.71 | 1238960 | 18.998 | | DG4 | 68.98 | 1202096 | 18.595 | | DG8 | 69.57 | 1183664 | 18.394 | | DG2S | 70.62 | 1238960 | 18.998 | | DG4S | 69.59 | 1202096 | 18.595 | | DG8S | 69.57 | 1183664 | 18.394 |
0
| Models | IOU | Params | GFLOPs | | --- | --- | --- | --- | | ERFNet | 70.45 | 2038448 | 27.705 | | D* | 68.55 | 547120 | 10.597 | | DG2* | 65.35 | 395568 | 8.852 | | DG4* | 61.42 | 319792 | 7.980 |
| DG8* | 59.15 | 281904 | 7.543 | | --- | --- | --- | --- | | DG2S* | 65.36 | 395568 | 8.852 | | DG4S* | 61.27 | 319792 | 7.980 | | DG8S* | 59.89 | 281904 | 7.543 |
1
| Models | IOU | Params | GFLOPs | | --- | --- | --- | --- | | ERFNet | 70.45 | 2038448 | 27.705 | | D* | 68.55 | 547120 | 10.597 | | DG2* | 65.35 | 395568 | 8.852 | | DG4* | 61.42 | 319792 | 7.980 |
| DG4 | 68.98 | 1202096 | 18.595 | | --- | --- | --- | --- | | DG8 | 69.57 | 1183664 | 18.394 | | DG2S | 70.62 | 1238960 | 18.998 | | DG4S | 69.59 | 1202096 | 18.595 | | DG8S | 69.57 | 1183664 | 18.394 |
0
| Feature | Type | | --- | --- | | Recency | ShallowLinguistic | | Frequency | ShallowLinguistic | | Grammaticalfunction | ShallowLinguistic | | Previoussubject | ShallowLinguistic | | Previousobject | ShallowLinguistic | | PreviousREtype | ShallowLinguistic |
| Selectionalpreferences | Linguistic | | --- | --- | | Participanttypefit | Script | | Predicateschemas | Script |
1
| Feature | Type | | --- | --- | | Recency | ShallowLinguistic | | Frequency | ShallowLinguistic | | Grammaticalfunction | ShallowLinguistic | | Previoussubject | ShallowLinguistic | | Previousobject | ShallowLinguistic | | PreviousREtype | ShallowLinguistic |
| 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
| Feature | Type | | --- | --- | | Recency | ShallowLinguistic | | Frequency | ShallowLinguistic | | Grammaticalfunction | ShallowLinguistic | | Previoussubject | ShallowLinguistic |
| Previousobject | ShallowLinguistic | | --- | --- | | PreviousREtype | ShallowLinguistic | | Selectionalpreferences | Linguistic | | Participanttypefit | Script | | Predicateschemas | Script |
1
| Feature | Type | | --- | --- | | Recency | ShallowLinguistic | | Frequency | ShallowLinguistic | | Grammaticalfunction | ShallowLinguistic | | Previoussubject | ShallowLinguistic |
| part-of-speech<br>phrasetype(VP/NP/PP)<br>dependencyrelations | | --- | | OtherFeatures | | speakerrole<br>topic |
0
| Model | ItautecMX214 | | --- | --- | | CPU | 2xIntelXeonX56753.07GHz | | DRAM | 48GBDDR31333MHz | | Disk | 5.8TBSATA3GB/s | | QPI | 6,4GT/s | | S.O. | Ubuntu15.04 | | Kernel | 3.19.0-15 |
| Hypervisor | KVM | | --- | --- | | HardwareEmulation | Qemu2.2.0 |
1
| Model | ItautecMX214 | | --- | --- | | CPU | 2xIntelXeonX56753.07GHz | | DRAM | 48GBDDR31333MHz | | Disk | 5.8TBSATA3GB/s | | QPI | 6,4GT/s | | S.O. | Ubuntu15.04 | | Kernel | 3.19.0-15 |
| ItemType | ItemDescription | Qty | | --- | --- | --- | | Chassis | NEXXUS4080ALDesk-sideChassis | 1 | | ComputeShelve | ComputeShelveAL/EN(IncludingPowerSupply) | 4 | | Motherboard | IntelS5000ALMotherboard-1333MHzFSB | 4 | | Processor | XeonQuad-CoreE54102.3312M1333MHz-80W | 8 | | MemoryType1 | 2GBFBDIMMSDDR2667ECC/...
0
| Model | ItautecMX214 | | --- | --- | | CPU | 2xIntelXeonX56753.07GHz | | DRAM | 48GBDDR31333MHz | | Disk | 5.8TBSATA3GB/s | | QPI | 6,4GT/s | | S.O. | Ubuntu15.04 |
| Kernel | 3.19.0-15 | | --- | --- | | Hypervisor | KVM | | HardwareEmulation | Qemu2.2.0 |
1
| Model | ItautecMX214 | | --- | --- | | CPU | 2xIntelXeonX56753.07GHz | | DRAM | 48GBDDR31333MHz | | Disk | 5.8TBSATA3GB/s | | QPI | 6,4GT/s | | S.O. | Ubuntu15.04 |
| HardDrive | HDDRaid500GB,7200rpm,16MB,SATAIINCQ | 2 | | --- | --- | --- | | HardDrive | HDDRaid250GB,7200rpm,16MB,SATAIINCQ | 3 | | HeatSink | HighPerformancePassiveHeatSink | 8 | | RiserCard | PCI/ExpressRiserCard | 4 | | KVM/USB | IntegratedKVM/USBSwitch | 1 | | GigabitSwitch | Integrated16PortGigESwitch | 1 | | Po...
0
| Parameter | Value | | --- | --- | | Stackedautoencoderinputlayerdim. | 1001 | | Stackedautoencodersecondlayerdim. | 91 |
| Stackedautoencoderbottlenecklayerdim. | 21 | | --- | --- | | Numberofhiddenlayers?? | 3 | | Firstlayeractivation | tanh | | Hiddenlayeractivation | sigmoid | | InitialstatesinHMM | 12-18 | | NumberofGMMcomponents | 2-5 | | MinimumdurationofHMMstates | 0.2s-1s | | Splicingcontext(past) | 5frames | | Splicingcontext(fu...
1
| Parameter | Value | | --- | --- | | Stackedautoencoderinputlayerdim. | 1001 | | Stackedautoencodersecondlayerdim. | 91 |
| LayerType | Parameters | | --- | --- | | Input | 94x24pixelsRGBimage | | Convolution | #643x3stride1 | | MaxPooling | #643x3stride1 | | Smallbasicblock | #1283x3stride1 | | MaxPooling | #643x3stride(2,1) | | Smallbasicblock | #2563x3stride1 | | Smallbasicblock | #2563x3stride1 | | MaxPooling | #643x3stride(2,1) | | D...
0
| Parameter | Value | | --- | --- | | Stackedautoencoderinputlayerdim. | 1001 | | Stackedautoencodersecondlayerdim. | 91 |
| Stackedautoencoderbottlenecklayerdim. | 21 | | --- | --- | | Numberofhiddenlayers?? | 3 | | Firstlayeractivation | tanh | | Hiddenlayeractivation | sigmoid | | InitialstatesinHMM | 12-18 | | NumberofGMMcomponents | 2-5 | | MinimumdurationofHMMstates | 0.2s-1s | | Splicingcontext(past) | 5frames | | Splicingcontext(fu...
1
| Parameter | Value | | --- | --- | | Stackedautoencoderinputlayerdim. | 1001 | | Stackedautoencodersecondlayerdim. | 91 |
| Convolution | #2564x1stride1 | | --- | --- | | Dropout | 0.5ratio | | Convolution | #classnumber1x13stride1 |
0
| \|Λ\|Algorithm | Objectivevaluesfordifferentp | | | | | --- | --- | --- | --- | --- | | p=0.9 | p=0.6 | p=0.5 | p=0.3 | p=0.1 |
| 10DCG<br>10Greedy | 7.1<br>6.8 | 5.2<br>5.1 | 4.7<br>4.6 | 3.4<br>3.4 | 2.6<br>2.6 | | --- | --- | --- | --- | --- | --- | | 50DCG<br>50Greedy | 7.4<br>6.82 | 5.84<br>5.66 | 5.18<br>5.06 | 3.98<br>3.98 | 2.68<br>2.68 | | 100DCG<br>100Greedy | 7.38<br>6.69 | 5.61<br>5.52 | 5.04<br>5.04 | 3.96<br>3.96 | 2.76<br>2.76 |
1
| \|Λ\|Algorithm | Objectivevaluesfordifferentp | | | | | --- | --- | --- | --- | --- | | p=0.9 | p=0.6 | p=0.5 | p=0.3 | p=0.1 |
| Pattern<br>Size | Algorithm | System1 | System2 | System3 | | --- | --- | --- | --- | --- | | 2 | ABM<br>HAL<br>L<br>SF<br>TBM | 8.89665<br>8.26117<br>6.08718<br>4.28357<br>10.5142 | 24.6946<br>24.6946<br>24.6946<br>9.87784<br>32.9261 | 32.9261<br>32.9261<br>32.9261<br>24.6946<br>32.9261 | | 4 | ABM<br>HAL<br>L<br>SF...
0
| \|Λ\|Algorithm | Objectivevaluesfordifferentp | | | | | --- | --- | --- | --- | --- | | p=0.9 | p=0.6 | p=0.5 | p=0.3 | p=0.1 |
| 10DCG<br>10Greedy | 7.1<br>6.8 | 5.2<br>5.1 | 4.7<br>4.6 | 3.4<br>3.4 | 2.6<br>2.6 | | --- | --- | --- | --- | --- | --- | | 50DCG<br>50Greedy | 7.4<br>6.82 | 5.84<br>5.66 | 5.18<br>5.06 | 3.98<br>3.98 | 2.68<br>2.68 | | 100DCG<br>100Greedy | 7.38<br>6.69 | 5.61<br>5.52 | 5.04<br>5.04 | 3.96<br>3.96 | 2.76<br>2.76 |
1
| \|Λ\|Algorithm | Objectivevaluesfordifferentp | | | | | --- | --- | --- | --- | --- | | p=0.9 | p=0.6 | p=0.5 | p=0.3 | p=0.1 |
| 8 | ABM<br>HAL<br>L<br>SF<br>TBM | 33.7463<br>37.0999<br>6.34086<br>4.23323<br>35.3437 | 69.2828<br>73.0482<br>26.6684<br>9.78229<br>72.2627 | 106.674<br>126.801<br>36.5241<br>22.0342<br>112.007 | | --- | --- | --- | --- | --- | | 10 | ABM<br>HAL<br>L<br>SF<br>TBM | 39.6329<br>42.5986<br>6.32525<br>4.22537<br>41.1973...
0
| Models | model1 | model2 | model3 | | --- | --- | --- | --- | | Trainingloss | 0.82 | 1.01 | 1.72 |
| Numberofepochs | 50 | 30 | 19 | | --- | --- | --- | --- | | BLEUscore | 24.5/9.0/3.2/1.3 | 26.0/9.7/3.6/1.5 | 26.4/10.1/3.8/1.6 | | METEORscore | 23.0 | 23.9 | 23.9 |
1
| Models | model1 | model2 | model3 | | --- | --- | --- | --- | | Trainingloss | 0.82 | 1.01 | 1.72 |
| Model | BLEU-1 | BLEU-2 | BLEU-3 | BLEU-4 | METEOR | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | c5 | c40 | c5 | c40 | c5 | c40 | c5 | c40 | c5 | c40 | c5 | | | SCN-LSTM | 0.740 | 0.917 | 0.575 | 0.839 | 0.436 | 0.739 | 0.331 | 0.631 | 0.257 | 0.348 | 0.543 | | ATT |...
0
| Models | model1 | model2 | model3 | | --- | --- | --- | --- | | Trainingloss | 0.82 | 1.01 | 1.72 | | Numberofepochs | 50 | 30 | 19 |
| BLEUscore | 24.5/9.0/3.2/1.3 | 26.0/9.7/3.6/1.5 | 26.4/10.1/3.8/1.6 | | --- | --- | --- | --- | | METEORscore | 23.0 | 23.9 | 23.9 |
1
| Models | model1 | model2 | model3 | | --- | --- | --- | --- | | Trainingloss | 0.82 | 1.01 | 1.72 | | Numberofepochs | 50 | 30 | 19 |
| ATT | 0.731 | 0.900 | 0.565 | 0.815 | 0.424 | 0.709 | 0.316 | 0.599 | 0.250 | 0.335 | 0.535 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | OV | 0.713 | 0.895 | 0.542 | 0.802 | 0.407 | 0.694 | 0.309 | 0.587 | 0.254 | 0.346 | 0.530 | | MSRCap | 0.715 | 0.907 | 0.543 | 0.819 | 0.407 | 0.71...
0
| | MetaCREST-01 | CREST-Base | CREST-10 | CREST-05 | CREST-03 | CREST-01 | | --- | --- | --- | --- | --- | --- | --- | | bag | 0.45 | 0.45 | 0.45 | 0.41 | 0.37 | 0.31 | | ball1 | 0.8 | 0.8 | 0.8 | 0.81 | 0.8 | 0.8 | | ball2 | 0.44 | 0.31 | 0.38 | 0.3 | 0.47 | 0.45 | | basketball | 0.6 | 0.55 | 0.55 | 0.6 | 0.62 | 0.6...
| motocross2 | 0.45 | 0.42 | 0.42 | 0.49 | 0.48 | 0.54 | | --- | --- | --- | --- | --- | --- | --- | | nature | 0.46 | 0.3 | 0.3 | 0.32 | 0.29 | 0.32 | | octopus | 0.4 | 0.32 | 0.33 | 0.44 | 0.43 | 0.37 | | pedestrian1 | 0.73 | 0.68 | 0.72 | 0.7 | 0.69 | 0.68 | | pedestrian2 | 0.3 | 0.45 | 0.49 | 0.38 | 0.37 | 0.34 | |...
1
| | MetaCREST-01 | CREST-Base | CREST-10 | CREST-05 | CREST-03 | CREST-01 | | --- | --- | --- | --- | --- | --- | --- | | bag | 0.45 | 0.45 | 0.45 | 0.41 | 0.37 | 0.31 | | ball1 | 0.8 | 0.8 | 0.8 | 0.81 | 0.8 | 0.8 | | ball2 | 0.44 | 0.31 | 0.38 | 0.3 | 0.47 | 0.45 | | basketball | 0.6 | 0.55 | 0.55 | 0.6 | 0.62 | 0.6...
| | MetaCREST-01 | CREST-Base | CREST-10 | CREST-05 | CREST-03 | CREST-01 | | --- | --- | --- | --- | --- | --- | --- | | bag | 0 | 0 | 0 | 0 | 0 | 0 | | ball1 | 0 | 0 | 0 | 0 | 0 | 0 | | ball2 | 1 | 0 | 0 | 0 | 1 | 1 | | basketball | 1 | 2 | 1.9 | 1 | 1 | 1 | | birds1 | 1 | 1 | 2 | 2 | 1 | 1 | | birds2 | 0 | 0 | 1 | ...
0
| | MetaCREST-01 | CREST-Base | CREST-10 | CREST-05 | CREST-03 | CREST-01 | | --- | --- | --- | --- | --- | --- | --- | | bag | 0.45 | 0.45 | 0.45 | 0.41 | 0.37 | 0.31 | | ball1 | 0.8 | 0.8 | 0.8 | 0.81 | 0.8 | 0.8 | | ball2 | 0.44 | 0.31 | 0.38 | 0.3 | 0.47 | 0.45 | | basketball | 0.6 | 0.55 | 0.55 | 0.6 | 0.62 | 0.6...
| pedestrian2 | 0.3 | 0.45 | 0.49 | 0.38 | 0.37 | 0.34 | | --- | --- | --- | --- | --- | --- | --- | | rabbit | 0.41 | 0.23 | 0.33 | 0.32 | 0.41 | 0.29 | | racing | 0.52 | 0.42 | 0.42 | 0.4 | 0.4 | 0.41 | | road | 0.58 | 0.58 | 0.57 | 0.62 | 0.64 | 0.67 | | shaking | 0.66 | 0.64 | 0.69 | 0.73 | 0.76 | 0.68 | | sheep | ...
1
| | MetaCREST-01 | CREST-Base | CREST-10 | CREST-05 | CREST-03 | CREST-01 | | --- | --- | --- | --- | --- | --- | --- | | bag | 0.45 | 0.45 | 0.45 | 0.41 | 0.37 | 0.31 | | ball1 | 0.8 | 0.8 | 0.8 | 0.81 | 0.8 | 0.8 | | ball2 | 0.44 | 0.31 | 0.38 | 0.3 | 0.47 | 0.45 | | basketball | 0.6 | 0.55 | 0.55 | 0.6 | 0.62 | 0.6...
| soccer1 | 2.93 | 3 | 2 | 2 | 1 | 1 | | --- | --- | --- | --- | --- | --- | --- | | soccer2 | 2 | 5 | 2 | 4 | 4 | 2 | | soldier | 1 | 1 | 1 | 1 | 1 | 1 | | sphere | 0 | 0 | 0 | 0 | 0 | 0 | | tiger | 0 | 0 | 0 | 0 | 0 | 0 | | traffic | 0 | 0 | 0 | 0 | 0 | 0.2 | | tunnel | 0 | 0 | 0 | 0 | 0 | 0 | | wiper | 0.4 | 0 | 0 |...
0
| Method | r | b | Total | | --- | --- | --- | --- | | VoronoiLSH(T=64) | 6 | 15 | 90 |
| CrossPolytope(T=64) | 6 | 18 | 108 | | --- | --- | --- | --- | | Hyperplane(T=6) | 5 | 22 | 110 | | FeatureHashing(T=64,k=1) | 7 | 16 | 112 | | FastCrossPolytope(T=64) | 6 | 15 | 90 | | DirectionalFeatureHashing(T=6) | 5 | 20 | 100 |
1
| Method | r | b | Total | | --- | --- | --- | --- | | VoronoiLSH(T=64) | 6 | 15 | 90 |
| Methods | mAP | | --- | --- | | Fast-RCNN+SRBBS | 55.7 | | Fast-RCNN+SRBBS+RBB | 69.6 | | Fast-RCNN+SRBBS+RBB+RRoI | 75.7 | | RRD(Ours) | 84.3 |
0
| Method | r | b | Total | | --- | --- | --- | --- | | VoronoiLSH(T=64) | 6 | 15 | 90 |
| CrossPolytope(T=64) | 6 | 18 | 108 | | --- | --- | --- | --- | | Hyperplane(T=6) | 5 | 22 | 110 | | FeatureHashing(T=64,k=1) | 7 | 16 | 112 | | FastCrossPolytope(T=64) | 6 | 15 | 90 | | DirectionalFeatureHashing(T=6) | 5 | 20 | 100 |
1
| Method | r | b | Total | | --- | --- | --- | --- | | VoronoiLSH(T=64) | 6 | 15 | 90 |
| Fast-RCNN+SRBBS+RBB+RRoI | 75.7 | | --- | --- | | RRD(Ours) | 84.3 |
0
| Ck | thek-thcluster | | --- | --- | | x | thepositionincanonicalframeforanodeofclusterCk | | y | thepositioninliveframetforanodeinclusterCk | | ck | thecentroidpositionofclusterCincanonicalframek | | c | thecentroidpositionofclusterCinliveframetk | | nk | thenumberofnodesbelongingtoclusterCincanonicalframek |
| A(C)k | thecrosscovariancematrixofclusterCk | | --- | --- | | (R,t) | rotationandtranslationofclusterCk | | (R,t) | optimalrotationandtranslationofclusterCk | | σkq | theq-thsingularvalueofA(C)k |
1
| Ck | thek-thcluster | | --- | --- | | x | thepositionincanonicalframeforanodeofclusterCk | | y | thepositioninliveframetforanodeinclusterCk | | ck | thecentroidpositionofclusterCincanonicalframek | | c | thecentroidpositionofclusterCinliveframetk | | nk | thenumberofnodesbelongingtoclusterCincanonicalframek |
| Abbreviation | Histogramofwhichplane | | --- | --- | | LBP-TOP | XY+XT+YT | | LBP-XYOT | XT+YT | | LBP-XOT | XT | | LBP-YOT | YT | | LBP | XY |
0
| Ck | thek-thcluster | | --- | --- | | x | thepositionincanonicalframeforanodeofclusterCk | | y | thepositioninliveframetforanodeinclusterCk | | ck | thecentroidpositionofclusterCincanonicalframek | | c | thecentroidpositionofclusterCinliveframetk | | nk | thenumberofnodesbelongingtoclusterCincanonicalframek |
| A(C)k | thecrosscovariancematrixofclusterCk | | --- | --- | | (R,t) | rotationandtranslationofclusterCk | | (R,t) | optimalrotationandtranslationofclusterCk | | σkq | theq-thsingularvalueofA(C)k |
1
| Ck | thek-thcluster | | --- | --- | | x | thepositionincanonicalframeforanodeofclusterCk | | y | thepositioninliveframetforanodeinclusterCk | | ck | thecentroidpositionofclusterCincanonicalframek | | c | thecentroidpositionofclusterCinliveframetk | | nk | thenumberofnodesbelongingtoclusterCincanonicalframek |
| LBP-XOT | XT | | --- | --- | | LBP-YOT | YT | | LBP | XY |
0
| | RFA/K-means | MSA/MRA | Relion | EMAN2 | Xmipp | ASPIRE | | --- | --- | --- | --- | --- | --- | --- | | SNR=1/50 | 0.45 | 0.97 | 0.79 | 0.74 | 0.83 | 1.00 | | SNR=1/100 | 0.09 | 0.87 | 0.70 | 0.45 | 0.68 | 0.99 |
| SNR=1/150 | 0.07 | 0.67 | 0.52 | 0.13 | 0.48 | 0.90 | | --- | --- | --- | --- | --- | --- | --- | | Timing(hrs) | 1.5 | 7.5 | 16 | 12 | 42 | 0.5 |
1
| | RFA/K-means | MSA/MRA | Relion | EMAN2 | Xmipp | ASPIRE | | --- | --- | --- | --- | --- | --- | --- | | SNR=1/50 | 0.45 | 0.97 | 0.79 | 0.74 | 0.83 | 1.00 | | SNR=1/100 | 0.09 | 0.87 | 0.70 | 0.45 | 0.68 | 0.99 |
| | noFBsPCAdenoising | FBsPCAdenoising | | --- | --- | --- | | RFA/K-means | 0.09 | 0.48 | | MSA/MRA | 0.87 | 0.95 | | EMAN2 | 0.45 | 0.76 | | Xmipp | 0.68 | 0.96 |
0
| | RFA/K-means | MSA/MRA | Relion | EMAN2 | Xmipp | ASPIRE | | --- | --- | --- | --- | --- | --- | --- | | SNR=1/50 | 0.45 | 0.97 | 0.79 | 0.74 | 0.83 | 1.00 | | SNR=1/100 | 0.09 | 0.87 | 0.70 | 0.45 | 0.68 | 0.99 |
| SNR=1/150 | 0.07 | 0.67 | 0.52 | 0.13 | 0.48 | 0.90 | | --- | --- | --- | --- | --- | --- | --- | | Timing(hrs) | 1.5 | 7.5 | 16 | 12 | 42 | 0.5 |
1
| | RFA/K-means | MSA/MRA | Relion | EMAN2 | Xmipp | ASPIRE | | --- | --- | --- | --- | --- | --- | --- | | SNR=1/50 | 0.45 | 0.97 | 0.79 | 0.74 | 0.83 | 1.00 | | SNR=1/100 | 0.09 | 0.87 | 0.70 | 0.45 | 0.68 | 0.99 |
| EMAN2 | 0.45 | 0.76 | | --- | --- | --- | | Xmipp | 0.68 | 0.96 |
0
| | | 1987-1995 | 2006-2008 | | --- | --- | --- | --- | | Books | different | 1984 | 2103 |
| conflict | 2528 | 2776 | | | --- | --- | --- | --- | | Newspaper | different | 1146 | 1661 | | conflict | 2368 | 3092 | |
1
| | | 1987-1995 | 2006-2008 | | --- | --- | --- | --- | | Books | different | 1984 | 2103 |
| Papers | Year | | --- | --- | | | 2005 | | | 2006 | | | 2007 | | | 2008 | | | 2010 | | | 2011 | | | 2012 | | | 2013 | | | 2014 | | | 2015 | | | 2016 | | | 2017 |
0
| | | 1987-1995 | 2006-2008 | | --- | --- | --- | --- | | Books | different | 1984 | 2103 |
| conflict | 2528 | 2776 | | | --- | --- | --- | --- | | Newspaper | different | 1146 | 1661 | | conflict | 2368 | 3092 | |
1
| | | 1987-1995 | 2006-2008 | | --- | --- | --- | --- | | Books | different | 1984 | 2103 |
| | 2016 | | --- | --- | | | 2017 |
0
| 2DConvolutional(filters=64,kernelsize=3,activation=”relu”,padding=”same”) | | --- | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=128,kernels...
| MaxPooling(poolsize=(2,2),strides=(2,2)) | | --- | | 2DConvolutional(filters=256,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=256,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=256,kernelsize=3,activation=“relu”,padding=“same”) | | MaxPooling(poolsize=(2,2),strid...
1
| 2DConvolutional(filters=64,kernelsize=3,activation=”relu”,padding=”same”) | | --- | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=128,kernels...
| 3DConvolutional(filters=32,kernelsize=5,strides=2,activation=”relu”) | | --- | | 3DConvolutional(filters=32,kernelsize=5,strides=2,activation=”relu”) | | MaxPooling3D(poolsize=(2,2),strides=(1,1)) | | 3DConvolutional(filters=32,kernelsize=3,strides=1,activation=”relu”) | | 3DConvolutional(filters=32,kernelsize=3,strides=...
0
| 2DConvolutional(filters=64,kernelsize=3,activation=”relu”,padding=”same”) | | --- | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=128,kernels...
| 2DConvolutional(filters=256,kernelsize=3,activation=“relu”,padding=“same”) | | --- | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=512,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=512,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=512,kern...
1
| 2DConvolutional(filters=64,kernelsize=3,activation=”relu”,padding=”same”) | | --- | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | 2DConvolutional(filters=64,kernelsize=3,activation=“relu”,padding=“same”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=128,kernels...
| 3DConvolutional(filters=32,kernelsize=3,strides=1,activation=”relu”) | | --- | | 3DConvolutional(filters=32,kernelsize=3,strides=1,activation=”relu”) | | MaxPooling3D(poolsize=(2,2),strides=(1,1)) | | Dense(128,activation=“relu”) | | Dense(64,activation=“relu”) | | Dense(1,activation=None) |
0
| n | tn | | --- | --- | | 8 | 560 | | 9 | 191520 | | 10 | 42058800 | | 11 | 7864256400 | | 12 | 1407126890400 | | 13 | 257752421166240 | | 14 | 50607986220311520 | | 15 | 10995419195575214400 | | 16 | 2692773804667509763200 |
| 17 | 747221542837742897724800 | | --- | --- | | 18 | 233698171655650029030743040 | | 19 | 81472765051132560093387934080 | | 20 | 31268587126068905034073041062400 |
1
| n | tn | | --- | --- | | 8 | 560 | | 9 | 191520 | | 10 | 42058800 | | 11 | 7864256400 | | 12 | 1407126890400 | | 13 | 257752421166240 | | 14 | 50607986220311520 | | 15 | 10995419195575214400 | | 16 | 2692773804667509763200 |
| n | tn | | --- | --- | | 8 | 560 | | 9 | 5040 | | 10 | 957600 | | 11 | 123354000 | | 12 | 16842764400 | | 13 | 2764379217600 | | 14 | 527554510282800 | | 15 | 114387072405606000 | | 16 | 27728561968887780000 | | 17 | 7418031804967840056000 | | 18 | 2167306256125914230527200 | | 19 | 685709965521372865035362400 | | 20...
0
| n | tn | | --- | --- | | 8 | 560 | | 9 | 191520 | | 10 | 42058800 | | 11 | 7864256400 | | 12 | 1407126890400 | | 13 | 257752421166240 | | 14 | 50607986220311520 | | 15 | 10995419195575214400 |
| 16 | 2692773804667509763200 | | --- | --- | | 17 | 747221542837742897724800 | | 18 | 233698171655650029030743040 | | 19 | 81472765051132560093387934080 | | 20 | 31268587126068905034073041062400 |
1
| n | tn | | --- | --- | | 8 | 560 | | 9 | 191520 | | 10 | 42058800 | | 11 | 7864256400 | | 12 | 1407126890400 | | 13 | 257752421166240 | | 14 | 50607986220311520 | | 15 | 10995419195575214400 |
| 14 | 527554510282800 | | --- | --- | | 15 | 114387072405606000 | | 16 | 27728561968887780000 | | 17 | 7418031804967840056000 | | 18 | 2167306256125914230527200 | | 19 | 685709965521372865035362400 | | 20 | 233306923207078035272369412000 |
0
| Method | NumberofPaths | RunningTime(ms) | | --- | --- | --- | | ILP | 2.0069 | 7.2133 | | RSG | 2.0160 | 2.0167 |
| RR | 2.0482 | 0.0272 | | --- | --- | --- | | MSPG | 2.2241 | 0.1911 | | EPS | 2.551 | 1.6000 |
1
| Method | NumberofPaths | RunningTime(ms) | | --- | --- | --- | | ILP | 2.0069 | 7.2133 | | RSG | 2.0160 | 2.0167 |
| method | AU01 | AU02 | AU04 | AU06 | AU09 | AU12 | AU25 | AU26 | avg | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | APL | 11.4 | 12.0 | 30.1 | 12.4 | 10.1 | 65.9 | 21.4 | 26.0 | 23.8 | | DRML | 17.3 | 17.7 | 37.4 | 29.0 | 10.7 | 37.7 | 38.5 | 20.1 | 26.7 | | ROI | 41.5 | 26.4 | 66.4 | 50.7 | 8.5 | ...
0
| Method | NumberofPaths | RunningTime(ms) | | --- | --- | --- | | ILP | 2.0069 | 7.2133 |
| RSG | 2.0160 | 2.0167 | | --- | --- | --- | | RR | 2.0482 | 0.0272 | | MSPG | 2.2241 | 0.1911 | | EPS | 2.551 | 1.6000 |
1
| Method | NumberofPaths | RunningTime(ms) | | --- | --- | --- | | ILP | 2.0069 | 7.2133 |
| DRML | 17.3 | 17.7 | 37.4 | 29.0 | 10.7 | 37.7 | 38.5 | 20.1 | 26.7 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ROI | 41.5 | 26.4 | 66.4 | 50.7 | 8.5 | 89.3 | 88.9 | 15.6 | 48.5 | | DSIN | [42.4] | [39.0] | [68.4] | 28.6 | [46.8] | 70.8 | [90.4] | [42.2] | [53.6] | | DSIN | 46.9 | 42.5 | 68.8 | ...
0
| FeatureType | datasetI | datasetII | | --- | --- | --- | | Extension | .url | .xls | | Extension | .properties | .txt | | Extension | .mdm | .html | | Extension | .pas | .net | | FileSize | - | - | | BytesUsed | - | - |
| Lastaccesstimediff | - | - | | --- | --- | --- | | Changetimediff | - | - | | Lastmodifiedtimediff | - | - | | Text | “feature” | “username” |
1
| FeatureType | datasetI | datasetII | | --- | --- | --- | | Extension | .url | .xls | | Extension | .properties | .txt | | Extension | .mdm | .html | | Extension | .pas | .net | | FileSize | - | - | | BytesUsed | - | - |
| Featurecategory | datasetI | datasetII | | --- | --- | --- | | Filename | 29736 | 14861 | | Filepath | 788 | 315 | | Fileextensions | 1170 | 316 | | Filesizerelated | 2 | 2 | | Timerelated | 3 | 3 | | Totalfeaturesize | 31699 | 15497 |
0
| FeatureType | datasetI | datasetII | | --- | --- | --- | | Extension | .url | .xls | | Extension | .properties | .txt | | Extension | .mdm | .html | | Extension | .pas | .net | | FileSize | - | - | | BytesUsed | - | - | | Lastaccesstimediff | - | - |
| Changetimediff | - | - | | --- | --- | --- | | Lastmodifiedtimediff | - | - | | Text | “feature” | “username” |
1
| FeatureType | datasetI | datasetII | | --- | --- | --- | | Extension | .url | .xls | | Extension | .properties | .txt | | Extension | .mdm | .html | | Extension | .pas | .net | | FileSize | - | - | | BytesUsed | - | - | | Lastaccesstimediff | - | - |
| Fileextensions | 1170 | 316 | | --- | --- | --- | | Filesizerelated | 2 | 2 | | Timerelated | 3 | 3 | | Totalfeaturesize | 31699 | 15497 |
0
| Input | Algorithm | Precision | Recall | F1 | | --- | --- | --- | --- | --- | | Rawfeaturevector | OCNN | 0.8029±0.1497 | 0.9075±0.0596 | 0.8383±0.0660 | | OCGP | 0.9700±0.0222 | 0.7308±0.0812 | 0.8302±0.0450 | | | OCSVM | 0.6590±0.0100 | 0.9404±0.0017 | 0.7749±0.0068 | |
| OCAN | 0.9755±0.0110 | 0.7416±0.0498 | 0.8416±0.0330 | | | --- | --- | --- | --- | --- | | Transactionrepresentation | OCNN | 0.7058±0.1396 | 0.9390±0.0786 | 0.7910±0.0608 | | OCGP | 0.8813±0.1177 | 0.8566±0.0822 | 0.8576±0.0417 | | | OCSVM | 0.6547±0.0151 | 0.9509±0.0101 | 0.7755±0.0127 | | | OCAN | 0.9067±0.0614...
1
| Input | Algorithm | Precision | Recall | F1 | | --- | --- | --- | --- | --- | | Rawfeaturevector | OCNN | 0.8029±0.1497 | 0.9075±0.0596 | 0.8383±0.0660 | | OCGP | 0.9700±0.0222 | 0.7308±0.0812 | 0.8302±0.0450 | | | OCSVM | 0.6590±0.0100 | 0.9404±0.0017 | 0.7749±0.0068 | |
| Input | Algorithm | Precision | Recall | F1 | | --- | --- | --- | --- | --- | | Rawfeaturevector | OCNN | 0.5680±0.0129 | 0.8646±0.0599 | 0.6845±0.0184 | | OCGP | 0.5767±0.0087 | 0.9000±0.0560 | 0.7023±0.0193 | | | OCSVM | 0.6631±0.0057 | 0.9829±0.0011 | 0.7919±0.0040 | | | Userrepresentation | OCNN | 0.8314±0.0351...
0
| Input | Algorithm | Precision | Recall | F1 | | --- | --- | --- | --- | --- | | Rawfeaturevector | OCNN | 0.8029±0.1497 | 0.9075±0.0596 | 0.8383±0.0660 |
| OCGP | 0.9700±0.0222 | 0.7308±0.0812 | 0.8302±0.0450 | | | --- | --- | --- | --- | --- | | OCSVM | 0.6590±0.0100 | 0.9404±0.0017 | 0.7749±0.0068 | | | OCAN | 0.9755±0.0110 | 0.7416±0.0498 | 0.8416±0.0330 | | | Transactionrepresentation | OCNN | 0.7058±0.1396 | 0.9390±0.0786 | 0.7910±0.0608 | | OCGP | 0.8813±0.1177...
1
| Input | Algorithm | Precision | Recall | F1 | | --- | --- | --- | --- | --- | | Rawfeaturevector | OCNN | 0.8029±0.1497 | 0.9075±0.0596 | 0.8383±0.0660 |
| Userrepresentation | OCNN | 0.8314±0.0351 | 0.8028±0.0476 | 0.8150±0.0163 | | --- | --- | --- | --- | --- | | OCGP | 0.8381±,0.0225 | 0.8289±0.0374 | 0.8326±0.0158 | | | OCSVM | 0.6558±0.0058 | 0.9590±0.0096 | 0.7789±0.0064 | | | OCAN | 0.9067±0.0615 | 0.9292±0.0348 | 0.9010±0.0228 | | | Userrepresentation | OCAN-...
0
| Strategy | RMSE±STD | Time | Nb | µ | | --- | --- | --- | --- | --- | | SK-Hype | 0.0006±0.0000 | 184.2852 | 188 | - | | GKKM | 0.0064±0.0000 | 17.0144 | 13 | 0.7982 |
| M=5,µ=0.2500,σ=0.09160 | | | | | | --- | --- | --- | --- | --- | | CCBS<br>GCBS | 0.0155±0.0002<br>0.0129±0.0001 | 13.5109<br>15.9691 | 9<br>9 | 0.2454<br>0.2454 | | M=30,µ=0.0345,σ=0.01740 | | | | | | CCBS<br>GCBS | 0.0101±0.0001<br>0.0102±0.0001 | 26.1530<br>26.1337 | 36<br>35 | 0.0336<br>0.0341 | | M=50,µ=...
1
| Strategy | RMSE±STD | Time | Nb | µ | | --- | --- | --- | --- | --- | | SK-Hype | 0.0006±0.0000 | 184.2852 | 188 | - | | GKKM | 0.0064±0.0000 | 17.0144 | 13 | 0.7982 |
| Strategy | RMSE±STD | Time | Nb | µ | | --- | --- | --- | --- | --- | | SK-Hype | 0.1320±0.0161 | 0.3034 | 211 | - | | GKKM | 0.1325±0.0150 | 1.8930 | 15 | 0.7694 | | M=5,µ=0.2500,σ=0.10840 | | | | | | CCBS<br>GCBS | 0.1358±0.0154<br>0.1585±0.0229 | 0.0550<br>0.0227 | 7<br>5 | 0.2441<br>0.2212 | | M=10,µ=0.1111,σ...
0
| Strategy | RMSE±STD | Time | Nb | µ | | --- | --- | --- | --- | --- | | SK-Hype | 0.0006±0.0000 | 184.2852 | 188 | - | | GKKM | 0.0064±0.0000 | 17.0144 | 13 | 0.7982 | | M=5,µ=0.2500,σ=0.09160 | | | | | | CCBS<br>GCBS | 0.0155±0.0002<br>0.0129±0.0001 | 13.5109<br>15.9691 | 9<br>9 | 0.2454<br>0.2454 | | M=30,µ=0.0...
| CCBS<br>GCBS | 0.0101±0.0001<br>0.0102±0.0001 | 26.1530<br>26.1337 | 36<br>35 | 0.0336<br>0.0341 | | --- | --- | --- | --- | --- | | M=50,µ=0.0204,σ=0.01130 | | | | | | CCBS<br>GCBS | 0.0099±0.0001<br>0.0092±0.0001 | 38.1907<br>19.4064 | 49<br>49 | 0.0199<br>0.0202 | | M=70,µ=0.0145,σ=0.00870 | | | | | | CCBS...
1
| Strategy | RMSE±STD | Time | Nb | µ | | --- | --- | --- | --- | --- | | SK-Hype | 0.0006±0.0000 | 184.2852 | 188 | - | | GKKM | 0.0064±0.0000 | 17.0144 | 13 | 0.7982 | | M=5,µ=0.2500,σ=0.09160 | | | | | | CCBS<br>GCBS | 0.0155±0.0002<br>0.0129±0.0001 | 13.5109<br>15.9691 | 9<br>9 | 0.2454<br>0.2454 | | M=30,µ=0.0...
| M=30,µ=0.0345,σ=0.02420 | | | | | | --- | --- | --- | --- | --- | | CCBS<br>GCBS | 0.1123±0.0131<br>0.1166±0.0143 | 0.1679<br>0.0248 | 29<br>28 | 0.0339<br>0.0323 |
0
| semantic | symbol | defaultvalue | | --- | --- | --- | | numberofnodes | n | 300sensors | | communicationradius | dtrx | 100meters | | sensingradius | ddtx | 25meters |
| targetspeed | detectionradius | 6km/h | | --- | --- | --- | | messagepropagationfrequency | freq | 1MSG/second | | networkdensity | dens | 10/(100·3.14)*Mag/second |
1
| semantic | symbol | defaultvalue | | --- | --- | --- | | numberofnodes | n | 300sensors | | communicationradius | dtrx | 100meters | | sensingradius | ddtx | 25meters |
| Parameters | Value | Description | | --- | --- | --- | | N | 1000 | Numberofvideocontents | | Ld | 30m | D2Ddistancethreshold | | Cd | 80 | CachesizeofD2Dtransmitusers | | Cf | 100∼500 | CachesizeofF-APs | | Bd | 300MHz | BandwidthofD2Dusers | | Bf | 100MHz | BandwidthofF-APs | | Pd | 13dBm | TransmitpowerofD2Dtransm...
0
| semantic | symbol | defaultvalue | | --- | --- | --- | | numberofnodes | n | 300sensors | | communicationradius | dtrx | 100meters | | sensingradius | ddtx | 25meters |
| targetspeed | detectionradius | 6km/h | | --- | --- | --- | | messagepropagationfrequency | freq | 1MSG/second | | networkdensity | dens | 10/(100·3.14)*Mag/second |
1
| semantic | symbol | defaultvalue | | --- | --- | --- | | numberofnodes | n | 300sensors | | communicationradius | dtrx | 100meters | | sensingradius | ddtx | 25meters |
| Pf | 23dBm | TransmitpowerofF-AP | | --- | --- | --- | | λru | −5<br>6×10 | Intensityofcontentrequireusers | | λtu | −5<br>5×10 | IntensityofD2Dtransmitusers | | λf | −5<br>3×10 | IntensityofF-APs | | λg | −6<br>2×10 | Intensityofgateways | | α | 4 | Pathlossexponent |
0
| LM | dev | eval | | | | --- | --- | --- | --- | --- | | Vit | CN | Vit | CN | | | ng4 | 30.4 | 29.8 | 31.0 | 30.7 |
| +uni-RNN | 28.5 | 27.8 | 28.7 | 28.4 | | --- | --- | --- | --- | --- | | +succ-RNN(1word)<br>+succ-RNN(3word) | 28.0<br>27.8 | 27.5<br>27.4 | 28.6<br>28.5 | 28.1<br>28.0 |
1
| LM | dev | eval | | | | --- | --- | --- | --- | --- | | Vit | CN | Vit | CN | | | ng4 | 30.4 | 29.8 | 31.0 | 30.7 |
| LM | #succ<br>words | dev | eval | | | | --- | --- | --- | --- | --- | --- | | Vit | CN | Vit | CN | | | | ng4 | - | 24.46 | 24.20 | 24.68 | 24.44 | | +uni-rnn | - | 22.49 | 22.33 | 22.53 | 22.30 | | +su-rnn | 1<br>3 | 22.32<br>21.97? | 22.13<br>21.77 | 22.20<br>21.70? | 22.09<br>21.53 |
0
| LM | dev | eval | | | | --- | --- | --- | --- | --- | | Vit | CN | Vit | CN | | | ng4 | 30.4 | 29.8 | 31.0 | 30.7 |
| +uni-RNN | 28.5 | 27.8 | 28.7 | 28.4 | | --- | --- | --- | --- | --- | | +succ-RNN(1word)<br>+succ-RNN(3word) | 28.0<br>27.8 | 27.5<br>27.4 | 28.6<br>28.5 | 28.1<br>28.0 |
1
| LM | dev | eval | | | | --- | --- | --- | --- | --- | | Vit | CN | Vit | CN | | | ng4 | 30.4 | 29.8 | 31.0 | 30.7 |
| +uni-rnn | - | 22.49 | 22.33 | 22.53 | 22.30 | | --- | --- | --- | --- | --- | --- | | +su-rnn | 1<br>3 | 22.32<br>21.97? | 22.13<br>21.77 | 22.20<br>21.70? | 22.09<br>21.53 |
0
| Dataset | AveragePoolMemory(inKBs) | | | | --- | --- | --- | --- | | | FCT | EPa | EP | | Flight | 32.1 | 20.2 | 18.1 | | Electricity | 31.6 | 16.1 | 14.1 |
| Rot.Hyperplane | 48.4 | 38.6 | 27.9 | | --- | --- | --- | --- | | Spam | 17.3 | 17.2 | 16.4 |
1
| Dataset | AveragePoolMemory(inKBs) | | | | --- | --- | --- | --- | | | FCT | EPa | EP | | Flight | 32.1 | 20.2 | 18.1 | | Electricity | 31.6 | 16.1 | 14.1 |
| Dataset | FCT | EPa | EP | | --- | --- | --- | --- | | Flight | 797.2 | 731.2 | 836.9 | | Electricity | 11600.3 | 9002.5 | 11402.5 | | RotatingHyperplane | 5647.8 | 5413.8 | 5804.5 | | Spam | 4.2 | 3.9 | 4.2 |
0
| Dataset | AveragePoolMemory(inKBs) | | | | --- | --- | --- | --- | | | FCT | EPa | EP | | Flight | 32.1 | 20.2 | 18.1 |
| Electricity | 31.6 | 16.1 | 14.1 | | --- | --- | --- | --- | | Rot.Hyperplane | 48.4 | 38.6 | 27.9 | | Spam | 17.3 | 17.2 | 16.4 |
1
| Dataset | AveragePoolMemory(inKBs) | | | | --- | --- | --- | --- | | | FCT | EPa | EP | | Flight | 32.1 | 20.2 | 18.1 |
| RotatingHyperplane | 5647.8 | 5413.8 | 5804.5 | | --- | --- | --- | --- | | Spam | 4.2 | 3.9 | 4.2 |
0
| 79.75(79.47,80.03) | 80.20(80.02,80.35) | 80.68(80.14,81.21) | 80.99(80.65,81.30) | | --- | --- | --- | --- | | 44.98(44.06,45.68) | 46.10(45.37,46.84) | 46.75(46.35,47.36) | 47.02(46.59,47.59) | | 83.69(83.46,84.07) | 84.63(84.44,84.88) | 85.18(84.64,85.59) | 85.38(85.31,85.49) |
| 92.60(92.28,92.76) | 92.87(92.69,93.17) | 93.06(92.81,93.19) | 93.13(92.79,93.32) | | --- | --- | --- | --- | | 90.29(89.93,90.61) | 91.42(91.16,91.71) | 91.52(91.23,91.72) | 91.47(91.15,91.64) | | 81.72(81.21,82.20) | 82.71(82.06,83.30) | 83.44(83.06,83.90) | 83.70(83.31,84.25) | | 89.15(88.83,89.47) | 89.39(89.14,8...
1
| 79.75(79.47,80.03) | 80.20(80.02,80.35) | 80.68(80.14,81.21) | 80.99(80.65,81.30) | | --- | --- | --- | --- | | 44.98(44.06,45.68) | 46.10(45.37,46.84) | 46.75(46.35,47.36) | 47.02(46.59,47.59) | | 83.69(83.46,84.07) | 84.63(84.44,84.88) | 85.18(84.64,85.59) | 85.38(85.31,85.49) |
| 79.22(79.02,79.57) | 45.46(44.88,45.96) | 83.24(82.93,83.67) | 91.97(91.64,92.17) | 85.86(85.54,86.13) | 80.24(79.64,80.62) | | --- | --- | --- | --- | --- | --- | | 80.27(79.94,80.51) | 46.18(45.74,46.52) | 84.37(83.96,94.70) | 92.83(92.58,93.06) | 90.33(90.05,90.62) | 80.71(79.72,81.37) | | 80.35(80.05,80.65) | 46....
0
| 79.75(79.47,80.03) | 80.20(80.02,80.35) | 80.68(80.14,81.21) | 80.99(80.65,81.30) | | --- | --- | --- | --- | | 44.98(44.06,45.68) | 46.10(45.37,46.84) | 46.75(46.35,47.36) | 47.02(46.59,47.59) | | 83.69(83.46,84.07) | 84.63(84.44,84.88) | 85.18(84.64,85.59) | 85.38(85.31,85.49) | | 92.60(92.28,92.76) | 92.87(92.69,9...
| 90.29(89.93,90.61) | 91.42(91.16,91.71) | 91.52(91.23,91.72) | 91.47(91.15,91.64) | | --- | --- | --- | --- | | 81.72(81.21,82.20) | 82.71(82.06,83.30) | 83.44(83.06,83.90) | 83.70(83.31,84.25) | | 89.15(88.83,89.47) | 89.39(89.14,89.56) | 89.30(89.16,89.60) | 89.37(88.99,89.61) |
1
| 79.75(79.47,80.03) | 80.20(80.02,80.35) | 80.68(80.14,81.21) | 80.99(80.65,81.30) | | --- | --- | --- | --- | | 44.98(44.06,45.68) | 46.10(45.37,46.84) | 46.75(46.35,47.36) | 47.02(46.59,47.59) | | 83.69(83.46,84.07) | 84.63(84.44,84.88) | 85.18(84.64,85.59) | 85.38(85.31,85.49) | | 92.60(92.28,92.76) | 92.87(92.69,9...
| 79.05(78.91,79.21) | 44.61(44.05,45.53) | 83.24(82.82,83.70) | 91.95(91.59,92.16) | 88.23(87.57,88.56) | 81.16(80.69,81.57) | | --- | --- | --- | --- | --- | --- | | 79.04(78.86,79.30) | 44.66(44.42,44.91) | 83.09(82.61,83.42) | 91.85(91.74,92.00) | 88.41(87.98,88.67) | 81.28(80.96,81.55) |
0
| | GradualandSharp | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Video | TP | FP | FN | P | R | F | | 01811a | 60 | 7 | 4 | 0.896 | 0.938 | 0.916 | | 6011 | 40 | 96 | 81 | 0.294 | 0.331 | 0.311 | | 8024 | 85 | 22 | 21 | 0.794 | 0.802 | 0.798 | | 8386 | 113 | 10 | 5 | 0.919 | 0.958 | 0.938 | | 8401 | ...
| UGS05 | 21 | 6 | 9 | 0.778 | 0.7 | 0.737 | | --- | --- | --- | --- | --- | --- | --- | | UGS09 | 169 | 12 | 24 | 0.934 | 0.876 | 0.904 | | Total | 1756 | 285 | 244 | 0.86 | 0.878 | 0.869 |
1
| | GradualandSharp | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Video | TP | FP | FN | P | R | F | | 01811a | 60 | 7 | 4 | 0.896 | 0.938 | 0.916 | | 6011 | 40 | 96 | 81 | 0.294 | 0.331 | 0.311 | | 8024 | 85 | 22 | 21 | 0.794 | 0.802 | 0.798 | | 8386 | 113 | 10 | 5 | 0.919 | 0.958 | 0.938 | | 8401 | ...
| | GradualandSharp | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Video | TP | FP | FN | P | R | F | | 01811a | 60 | 7 | 4 | 0.896 | 0.938 | 0.916 | | 6011 | 39 | 96 | 82 | 0.289 | 0.322 | 0.305 | | 8024 | 96 | 29 | 10 | 0.768 | 0.906 | 0.831 | | 8386 | 114 | 5 | 4 | 0.958 | 0.966 | 0.962 | | 8401 | 3...
0
| | GradualandSharp | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Video | TP | FP | FN | P | R | F | | 01811a | 60 | 7 | 4 | 0.896 | 0.938 | 0.916 | | 6011 | 40 | 96 | 81 | 0.294 | 0.331 | 0.311 | | 8024 | 85 | 22 | 21 | 0.794 | 0.802 | 0.798 | | 8386 | 113 | 10 | 5 | 0.919 | 0.958 | 0.938 |
| 8401 | 26 | 5 | 5 | 0.839 | 0.839 | 0.839 | | --- | --- | --- | --- | --- | --- | --- | | 10558a | 122 | 1 | 8 | 0.992 | 0.938 | 0.964 | | 23585a | 149 | 10 | 16 | 0.937 | 0.903 | 0.92 | | 23585b | 103 | 3 | 1 | 0.972 | 0.99 | 0.981 | | 34921a | 70 | 4 | 5 | 0.946 | 0.933 | 0.94 | | 34921b | 91 | 10 | 8 | 0.901 | 0.9...
1
| | GradualandSharp | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Video | TP | FP | FN | P | R | F | | 01811a | 60 | 7 | 4 | 0.896 | 0.938 | 0.916 | | 6011 | 40 | 96 | 81 | 0.294 | 0.331 | 0.311 | | 8024 | 85 | 22 | 21 | 0.794 | 0.802 | 0.798 | | 8386 | 113 | 10 | 5 | 0.919 | 0.958 | 0.938 |
| UGS04 | 222 | 15 | 1 | 0.937 | 0.996 | 0.965 | | --- | --- | --- | --- | --- | --- | --- | | UGS05 | 26 | 21 | 4 | 0.553 | 0.867 | 0.675 | | UGS09 | 176 | 17 | 17 | 0.912 | 0.912 | 0.912 | | Total | 1827 | 313 | 173 | 0.854 | 0.913 | 0.883 |
0