premise string | hypothesis string | label int64 |
|---|---|---|
| Scheme | 1 | 2 | 3 | 4 |
| --- | --- | --- | --- | --- |
| N(sizeofthesystem) | 8 | 8 | 8 | 5 |
| M | {1} | {8} | {1,..,8} | {4,5} |
| Frequency(Monobit)Test | 0 | 0.289667 | 0 | 0.108791 |
| FrequencyTestwithinaBlock(M=20000) | 0 | 0 | 0 | 0.699313 |
| RunsTest | 0 | 0.955835 | 0.816537 | 0.739918 |
| TestfortheLong... | | Maurer’s“UniversalStatistical”Test(L=7,Q=1280) | 0 | 0.075719 | 0.080519 | 0.102526 |
| --- | --- | --- | --- | --- |
| LinearComplexityTest(M=500) | 0.955835 | 0.474986 | 0.051942 | 0.023545 |
| SerialTest*(m=10) | 0 | 0 | 0 | 0.308152 |
| ApproximateEntropyTest(m=10) | 0 | 0 | 0 | 0 |
| CumulativeSums(Cusum)Test* |... | 1 |
| Scheme | 1 | 2 | 3 | 4 |
| --- | --- | --- | --- | --- |
| N(sizeofthesystem) | 8 | 8 | 8 | 5 |
| M | {1} | {8} | {1,..,8} | {4,5} |
| Frequency(Monobit)Test | 0 | 0.289667 | 0 | 0.108791 |
| FrequencyTestwithinaBlock(M=20000) | 0 | 0 | 0 | 0.699313 |
| RunsTest | 0 | 0.955835 | 0.816537 | 0.739918 |
| TestfortheLong... | | Method | CIPRNG | XORshift | BBS |
| --- | --- | --- | --- |
| Frequency(Monobit)Test | 0.073128 | 0.145326 | 0.32435 |
| FrequencyTestwithinaBlock | 0.719128 | 0.028817 | 0.000000 |
| RunsTest | 0.314992 | 0.739918 | 0.000000 |
| LongestRunofOnesinaBlockTest | 0.445121 | 0.554420 | 0.000000 |
| BinaryMatrixRankTest ... | 0 |
| Scheme | 1 | 2 | 3 | 4 |
| --- | --- | --- | --- | --- |
| N(sizeofthesystem) | 8 | 8 | 8 | 5 |
| M | {1} | {8} | {1,..,8} | {4,5} |
| Frequency(Monobit)Test | 0 | 0.289667 | 0 | 0.108791 |
| FrequencyTestwithinaBlock(M=20000) | 0 | 0 | 0 | 0.699313 |
| RunsTest | 0 | 0.955835 | 0.816537 | 0.739918 |
| TestfortheLong... | | RandomExcursionsTest* | 0.015102 | 0.45675 | 0.194299 | 0.293228 |
| --- | --- | --- | --- | --- |
| RandomExcursionsVariantTest* | 0.045440 | 0.49615 | 0.145418 | 0.330716 |
| Success | 3/15 | 7/15 | 6/15 | 14/15 | | 1 |
| Scheme | 1 | 2 | 3 | 4 |
| --- | --- | --- | --- | --- |
| N(sizeofthesystem) | 8 | 8 | 8 | 5 |
| M | {1} | {8} | {1,..,8} | {4,5} |
| Frequency(Monobit)Test | 0 | 0.289667 | 0 | 0.108791 |
| FrequencyTestwithinaBlock(M=20000) | 0 | 0 | 0 | 0.699313 |
| RunsTest | 0 | 0.955835 | 0.816537 | 0.739918 |
| TestfortheLong... | | LinearComplexityTest | 0.475761 | 0.249284 | 0.000000 |
| --- | --- | --- | --- |
| SerialTest*(m=10) | 0.780099 | 0.495847 | 0.043355 |
| ApproximateEntropyTest(m=10) | 0.679102 | 0.000000 | 0.000000 |
| CumulativeSums(Cusum)Test* | 0.819200 | 0.074404 | 0.000000 |
| RandomExcursionsTest* | 0.697803 | 0.507812 | 0.0... | 0 |
| Variable | Description | Type | Scale | Category |
| --- | --- | --- | --- | --- |
| ClonesetID<br>Capturetime<br>Uploadtime<br>Updatetime<br>Categoriescount | Uniqueclonesetidentifier<br>Timeatwhichthisvideodatawascaptured<br>Timeatwhichthevideowasfirstpublished<br>Timeatwhichthevideowaslastupdated<br>Numberofcatego... | | Uploaderage<br>Uploadercontacts<br>Uploaderfollowers<br>Uploadervideocount<br>Uploaderviewcount | Ageoftheuploader<br>Numberof(YouTube)’friends’oftheuploader<br>Numberoffollowersfortheuploader<br>Numberofvideosuploadedbytheuploader<br>Numberoftimeanyoftheuploader’svideoswereviewed | Predictor<br>Predictor<br>Predicto... | 1 |
| Variable | Description | Type | Scale | Category |
| --- | --- | --- | --- | --- |
| ClonesetID<br>Capturetime<br>Uploadtime<br>Updatetime<br>Categoriescount | Uniqueclonesetidentifier<br>Timeatwhichthisvideodatawascaptured<br>Timeatwhichthevideowasfirstpublished<br>Timeatwhichthevideowaslastupdated<br>Numberofcatego... | | TextRetrievalDatasets | | | |
| --- | --- | --- | --- |
| Label | Description | #queries | #images |
| IC11 | ICDAR2011testdataset. | 538 | 255 |
| SVT | SVTtestdataset. | 427 | 249 |
| STR | IIITSTRtextretrievaldataset. | 50 | 10k |
| Sports | IIITSports-10ktextretrievaldataset. | 10 | 10k |
| BBCNews | Adataseto... | 0 |
| Variable | Description | Type | Scale | Category |
| --- | --- | --- | --- | --- |
| ClonesetID<br>Capturetime<br>Uploadtime<br>Updatetime<br>Categoriescount | Uniqueclonesetidentifier<br>Timeatwhichthisvideodatawascaptured<br>Timeatwhichthevideowasfirstpublished<br>Timeatwhichthevideowaslastupdated<br>Numberofcatego... | | Ratingaverage<br>Totalcomments<br>Totaldislikes<br>Totalfavourites<br>Totallikes<br>Totalratings<br>Totalviewcount | Averagerating(minandmaxratingsalsomeasured)<br>Numberofcomments<br>Numberof’dislike’events<br>Numberoftimethisvideowas’favourited’<br>Numberof’like’events<br>Numberofratings<br>Numberofviews | Predicto... | 1 |
| Variable | Description | Type | Scale | Category |
| --- | --- | --- | --- | --- |
| ClonesetID<br>Capturetime<br>Uploadtime<br>Updatetime<br>Categoriescount | Uniqueclonesetidentifier<br>Timeatwhichthisvideodatawascaptured<br>Timeatwhichthevideowasfirstpublished<br>Timeatwhichthevideowaslastupdated<br>Numberofcatego... | | IC11 | ICDAR2011testdataset. | 538 | 255 |
| --- | --- | --- | --- |
| SVT | SVTtestdataset. | 427 | 249 |
| STR | IIITSTRtextretrievaldataset. | 50 | 10k |
| Sports | IIITSports-10ktextretrievaldataset. | 10 | 10k |
| BBCNews | AdatasetofkeyframesfromBBCNewsvideo. | - | 2.3m | | 0 |
| | σ=10 | σ=20 | σ=30 | σ=40 | σ=50 |
| --- | --- | --- | --- | --- | --- |
| KSVDG | 33.57 | 30.18 | 28.83 | 26.43 | 25.32 |
| KSVDS | 34.23 | 31.02 | 28.94 | 26.66 | 25.48 |
| KSVDC | 34.46 | 32.24 | 29.62 | 26.76 | 25.67 | | | SCFW | 34.83 | 33.45 | 30.28 | 26.27 | 25.32 |
| --- | --- | --- | --- | --- | --- |
| SCLW | 36.27 | 34.24 | 32.83 | 28.76 | 26.32 | | 1 |
| | σ=10 | σ=20 | σ=30 | σ=40 | σ=50 |
| --- | --- | --- | --- | --- | --- |
| KSVDG | 33.57 | 30.18 | 28.83 | 26.43 | 25.32 |
| KSVDS | 34.23 | 31.02 | 28.94 | 26.66 | 25.48 |
| KSVDC | 34.46 | 32.24 | 29.62 | 26.76 | 25.67 | | | | σ=10 | σ=20 | σ=30 | σ=40 | σ=50 |
| --- | --- | --- | --- | --- | --- |
| r=0 | 30.47 | 28.48 | 27.67 | 26.20 | 24.06 |
| r=1 | 32.23 | 30.27 | 29.95 | 26.82 | 25.03 |
| r=3 | 35.46 | 33.27 | 31.80 | 28.97 | 26.21 |
| r=4 | 36.27 | 34.24 | 32.83 | 28.76 | 26.32 |
| r=7 | 36.18 | 34.05 | 32.58 | 28.94 | 26.37 |
| ... | 0 |
| | σ=10 | σ=20 | σ=30 | σ=40 | σ=50 |
| --- | --- | --- | --- | --- | --- |
| KSVDG | 33.57 | 30.18 | 28.83 | 26.43 | 25.32 | | | KSVDS | 34.23 | 31.02 | 28.94 | 26.66 | 25.48 |
| --- | --- | --- | --- | --- | --- |
| KSVDC | 34.46 | 32.24 | 29.62 | 26.76 | 25.67 |
| SCFW | 34.83 | 33.45 | 30.28 | 26.27 | 25.32 |
| SCLW | 36.27 | 34.24 | 32.83 | 28.76 | 26.32 | | 1 |
| | σ=10 | σ=20 | σ=30 | σ=40 | σ=50 |
| --- | --- | --- | --- | --- | --- |
| KSVDG | 33.57 | 30.18 | 28.83 | 26.43 | 25.32 | | | r=9 | 36.07 | 33.84 | 31.73 | 28.31 | 26.02 |
| --- | --- | --- | --- | --- | --- |
| r=15 | 34.57 | 31.28 | 30.80 | 27.67 | 25.83 | | 0 |
| Dataset | Initialalarms | Aggregatedalarms |
| --- | --- | --- |
| A | 129 | 16 |
| B | 658 | 21 |
| C | 9273 | 18 | | | D | 203 | 16 |
| --- | --- | --- |
| All | 10507 | 22 | | 1 |
| Dataset | Initialalarms | Aggregatedalarms |
| --- | --- | --- |
| A | 129 | 16 |
| B | 658 | 21 |
| C | 9273 | 18 | | | method | datasetA | datasetB |
| --- | --- | --- |
| ES | 4.32 | 7.02 |
| ES4LT | 0.97 | 3.59 |
| MD | 11.30 | 22.82 |
| MD4LT | 1.63 | 1.25 |
| VO | 4.49 | 17.19 |
| VO4LT | 1.86 | 3.05 | | 0 |
| Dataset | Initialalarms | Aggregatedalarms |
| --- | --- | --- |
| A | 129 | 16 | | | B | 658 | 21 |
| --- | --- | --- |
| C | 9273 | 18 |
| D | 203 | 16 |
| All | 10507 | 22 | | 1 |
| Dataset | Initialalarms | Aggregatedalarms |
| --- | --- | --- |
| A | 129 | 16 | | | VO | 4.49 | 17.19 |
| --- | --- | --- |
| VO4LT | 1.86 | 3.05 | | 0 |
| Metric | Value |
| --- | --- |
| NumberofFilers | 2,080 |
| NumberofFilings | 2,175 |
| NumberofFilingDocuments | 224,187 |
| TimetoRun | 24hrs | | | SizeofRawDocuments | 3.7GB |
| --- | --- |
| SizeofExtractedText | 1.7GB | | 1 |
| Metric | Value |
| --- | --- |
| NumberofFilers | 2,080 |
| NumberofFilings | 2,175 |
| NumberofFilingDocuments | 224,187 |
| TimetoRun | 24hrs | | | Metric | Description |
| --- | --- |
| Executiontime | Measuredinseconds |
| CPUusage | TotalCPUtimepersecond |
| Totalmemorysize | MeasuredinGB |
| CPI | Cyclesperinstruction |
| MAI | Thenumberofmemoryaccesses<br>perinstruction | | 0 |
| Metric | Value |
| --- | --- |
| NumberofFilers | 2,080 |
| NumberofFilings | 2,175 | | | NumberofFilingDocuments | 224,187 |
| --- | --- |
| TimetoRun | 24hrs |
| SizeofRawDocuments | 3.7GB |
| SizeofExtractedText | 1.7GB | | 1 |
| Metric | Value |
| --- | --- |
| NumberofFilers | 2,080 |
| NumberofFilings | 2,175 | | | Totalmemorysize | MeasuredinGB |
| --- | --- |
| CPI | Cyclesperinstruction |
| MAI | Thenumberofmemoryaccesses<br>perinstruction | | 0 |
| Architectures | Accuracy | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Neutral | Anger | Disgust | Fear | Happy | Sad | Surprise | Total |
| VGG-16 | 0.327 | 0.424 | 0.102 | 0.093 | 0.476 | 0.138 | 0.133 | 0.263 |
| VGG-16+RNN | 0.431 | 0.559 | 0.026 | 0.07 | 0.444 | 0.259 | 0.04... | | ResNet | 0.31 | 0.153 | 0.077 | 0.023 | 0.534 | 0.207 | 0.067 | 0.211 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ResNet+RNN | 0.431 | 0.237 | 0.077 | 0.07 | 0.587 | 0.155 | 0.089 | 0.261 |
| VGG-Face+RNN | 0.552 | 0.593 | 0.026 | 0.047 | 0.794 | 0.259 | 0.111 | 0.384 |
| fine-tunedAffWildNet | 0.569 | ... | 1 |
| Architectures | Accuracy | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Neutral | Anger | Disgust | Fear | Happy | Sad | Surprise | Total |
| VGG-16 | 0.327 | 0.424 | 0.102 | 0.093 | 0.476 | 0.138 | 0.133 | 0.263 |
| VGG-16+RNN | 0.431 | 0.559 | 0.026 | 0.07 | 0.444 | 0.259 | 0.04... | | | Mean | Neutral | Calm | Happy | Sad | Angry | Fearful | Disgu. | Surpri. |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| LSTM | 1.039 | 1.059 | 1.039 | 1.082 | 1.010 | 1.033 | 1.016 | 1.049 | 1.038 |
| CNN-static | 0.741 | 0.725 | 0.715 | 0.760 | 0.728 | 0.746 | 0.746 | 0.781 | 0.746 |
| CNN+LSTM... | 0 |
| Architectures | Accuracy | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Neutral | Anger | Disgust | Fear | Happy | Sad | Surprise | Total |
| VGG-16 | 0.327 | 0.424 | 0.102 | 0.093 | 0.476 | 0.138 | 0.133 | 0.263 |
| VGG-16+RNN | 0.431 | 0.559 | 0.026 | 0.07 | 0.444 | 0.259 | 0.04... | | ResNet+RNN | 0.431 | 0.237 | 0.077 | 0.07 | 0.587 | 0.155 | 0.089 | 0.261 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| VGG-Face+RNN | 0.552 | 0.593 | 0.026 | 0.047 | 0.794 | 0.259 | 0.111 | 0.384 |
| fine-tunedAffWildNet | 0.569 | 0.627 | 0.051 | 0.023 | 0.746 | 0.709 | 0.111 | 0.454 | | 1 |
| Architectures | Accuracy | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Neutral | Anger | Disgust | Fear | Happy | Sad | Surprise | Total |
| VGG-16 | 0.327 | 0.424 | 0.102 | 0.093 | 0.476 | 0.138 | 0.133 | 0.263 |
| VGG-16+RNN | 0.431 | 0.559 | 0.026 | 0.07 | 0.444 | 0.259 | 0.04... | | CNN+LSTM | 1.042 | 1.077 | 1.029 | 1.092 | 1.029 | 1.013 | 1.031 | 1.035 | 1.054 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| CNN+GRU | 1.022 | 1.034 | 0.995 | 1.081 | 0.999 | 1.012 | 1.008 | 1.023 | 1.045 | | 0 |
| | DiscontinuityComponents | | |
| --- | --- | --- | --- |
| Value | d.x | d.y | d.z |
| 0 | Noedge | Noedge | Litfragment |
| 0.25 | Right-sideedge | Top-sideedge | – |
| 0.5 | Left-sideedge | Bottom-sideedge | – | | | 0.75 | Left-right-sideedge | Top-bottom-sideedge | – |
| --- | --- | --- | --- |
| 1 | – | – | Shadowedfragment | | 1 |
| | DiscontinuityComponents | | |
| --- | --- | --- | --- |
| Value | d.x | d.y | d.z |
| 0 | Noedge | Noedge | Litfragment |
| 0.25 | Right-sideedge | Top-sideedge | – |
| 0.5 | Left-sideedge | Bottom-sideedge | – | | | Symbol | Meaning | Separatingdistance |
| --- | --- | --- |
| E | Entropy | 2.0267 |
| B | Totalnon-zerohistogrambins | 1.7142 |
| M2 | Secondordercentralmoment | 1.5166 |
| Γ(h)4 | Rightdiagonaledge | 1.2329 |
| Γ(h)3 | Leftdiagonaledge | 1.2047 |
| M1 | Firstordermoment(mean) | 0.8501 |
| Γ(h)2 | Verticaledge | 0.7... | 0 |
| | DiscontinuityComponents | | |
| --- | --- | --- | --- |
| Value | d.x | d.y | d.z | | | 0 | Noedge | Noedge | Litfragment |
| --- | --- | --- | --- |
| 0.25 | Right-sideedge | Top-sideedge | – |
| 0.5 | Left-sideedge | Bottom-sideedge | – |
| 0.75 | Left-right-sideedge | Top-bottom-sideedge | – |
| 1 | – | – | Shadowedfragment | | 1 |
| | DiscontinuityComponents | | |
| --- | --- | --- | --- |
| Value | d.x | d.y | d.z | | | Γ(h)4 | Rightdiagonaledge | 1.2329 |
| --- | --- | --- |
| Γ(h)3 | Leftdiagonaledge | 1.2047 |
| M1 | Firstordermoment(mean) | 0.8501 |
| Γ(h)2 | Verticaledge | 0.7979 |
| Γ(h)1 | Horizontaledge | 0.8353 | | 0 |
| Description | B3<br>PRF | Pairwise<br>PRF |
| --- | --- | --- |
| Baseline | 0.99010.97600.9830 | 0.99480.97380.9842 |
| Blocking=SFI<br>Blocking=Doublemetaphone<br>Blocking=NYSIIS<br>Blocking=Soundex | 0.99010.97600.9830<br>0.98560.98270.9841<br>0.98750.98260.9850<br>0.98860.97450.9815 | 0.99480.97380.9842<br>0.9927... | | Trainingpairs=Non-blocked,uniform<br>Trainingpairs=Blocked,uniform<br>Trainingpairs=Blocked,balanced | 0.97930.96300.9711<br>0.98540.97200.9786<br>0.99010.97600.9830 | 0.97560.96290.9692<br>0.98500.97070.9778<br>0.99480.97380.9842 |
| --- | --- | --- |
| Clustering=Averagelinkage<br>Clustering=Singlelinkage<br>Cluste... | 1 |
| Description | B3<br>PRF | Pairwise<br>PRF |
| --- | --- | --- |
| Baseline | 0.99010.97600.9830 | 0.99480.97380.9842 |
| Blocking=SFI<br>Blocking=Doublemetaphone<br>Blocking=NYSIIS<br>Blocking=Soundex | 0.99010.97600.9830<br>0.98560.98270.9841<br>0.98750.98260.9850<br>0.98860.97450.9815 | 0.99480.97380.9842<br>0.9927... | | Scale | Bicubic<br>PSNR/SSIM | A+<br>PSNR/SSIM | RFL<br>PSNR/SSIM | SelfEx<br>PSNR/SSIM | SRCNN<br>PSNR/SSIM |
| --- | --- | --- | --- | --- | --- |
| ×2<br>×3<br>×4 | 33.66/0.9299<br>30.39/0.8682<br>28.42/0.8104 | 36.54/0.9544<br>32.58/0.9088<br>30.28/0.8603 | 36.54/0.9537<br>32.43/0.9057<br>30.14/0.8548 | 36.49/0.9... | 0 |
| Description | B3<br>PRF | Pairwise<br>PRF |
| --- | --- | --- |
| Baseline | 0.99010.97600.9830 | 0.99480.97380.9842 |
| Blocking=SFI<br>Blocking=Doublemetaphone<br>Blocking=NYSIIS<br>Blocking=Soundex | 0.99010.97600.9830<br>0.98560.98270.9841<br>0.98750.98260.9850<br>0.98860.97450.9815 | 0.99480.97380.9842<br>0.9927... | | Classifier=GBRT<br>Classifier=RandomForests<br>Classifier=LinearRegression | 0.99010.97600.9830<br>0.99090.97830.9846<br>0.97490.95840.9666 | 0.99480.97380.9842<br>0.99570.97520.9854<br>0.97170.95690.9643 |
| --- | --- | --- |
| Trainingpairs=Non-blocked,uniform<br>Trainingpairs=Blocked,uniform<br>Trainingpairs=Blocked,... | 1 |
| Description | B3<br>PRF | Pairwise<br>PRF |
| --- | --- | --- |
| Baseline | 0.99010.97600.9830 | 0.99480.97380.9842 |
| Blocking=SFI<br>Blocking=Doublemetaphone<br>Blocking=NYSIIS<br>Blocking=Soundex | 0.99010.97600.9830<br>0.98560.98270.9841<br>0.98750.98260.9850<br>0.98860.97450.9815 | 0.99480.97380.9842<br>0.9927... | | ×2<br>×3<br>×4 | 29.56/0.8431<br>27.21/0.7385<br>25.96/0.6675 | 31.21/0.8863<br>28.29/0.7835<br>26.82/0.7087 | 31.16/0.8840<br>28.22/0.7806<br>26.75/0.7054 | 31.18/0.8855<br>28.29/0.7840<br>26.84/0.7106 | 31.36/0.8879<br>28.41/0.7863<br>26.90/0.7101 |
| --- | --- | --- | --- | --- | --- |
| ×2<br>×3<br>×4 | 26.88/0.8... | 0 |
| Dataset | #Instances | #Features |
| --- | --- | --- |
| Synthetic | 500 | 10 |
| CAPTCHA | 1886 | 26 | | | Phishing | 11055 | 46 |
| --- | --- | --- |
| Digits08 | 1499 | 16 |
| Digits17 | 1557 | 16 | | 1 |
| Dataset | #Instances | #Features |
| --- | --- | --- |
| Synthetic | 500 | 10 |
| CAPTCHA | 1886 | 26 | | | Dataset | #Instances | #Dimensions |
| --- | --- | --- |
| Digits08 | 1500 | 16 |
| Credit | 1000 | 61 |
| Cancer | 699 | 10 |
| Qsar | 1055 | 41 |
| Sonar | 208 | 60 |
| Theorem | 3060 | 51 |
| Diabetes | 768 | 8 |
| Spambase | 4600 | 57 |
| KDD99 | 494021 | 41 |
| CAPTCHA | 1885 | 26 | | 0 |
| Dataset | #Instances | #Features |
| --- | --- | --- |
| Synthetic | 500 | 10 | | | CAPTCHA | 1886 | 26 |
| --- | --- | --- |
| Phishing | 11055 | 46 |
| Digits08 | 1499 | 16 |
| Digits17 | 1557 | 16 | | 1 |
| Dataset | #Instances | #Features |
| --- | --- | --- |
| Synthetic | 500 | 10 | | | KDD99 | 494021 | 41 |
| --- | --- | --- |
| CAPTCHA | 1885 | 26 | | 0 |
| reference | quantity |
| --- | --- |
| T-shirt | 5 | | | Jeans | 10 |
| --- | --- |
| Soda | 2 |
| Friedpotatoes | 1 |
| Water | 12 | | 1 |
| reference | quantity |
| --- | --- |
| T-shirt | 5 | | | reference | Day1 | Day2 | Day3 | ··· | Day365 |
| --- | --- | --- | --- | --- | --- |
| T-shirt | 100 | 150 | 63 | ··· | 45 |
| Jeans | 50 | 96 | 7 | ··· | 33 |
| Soda | 45 | 35 | 14 | ··· | 10 |
| Friedpotatoes | 36 | 23 | 23 | ··· | 5 |
| Water | 85 | 75 | 78 | ··· | 20 | | 0 |
| reference | quantity |
| --- | --- |
| T-shirt | 5 | | | Jeans | 10 |
| --- | --- |
| Soda | 2 |
| Friedpotatoes | 1 |
| Water | 12 | | 1 |
| reference | quantity |
| --- | --- |
| T-shirt | 5 | | | Jeans | 50 | 96 | 7 | ··· | 33 |
| --- | --- | --- | --- | --- | --- |
| Soda | 45 | 35 | 14 | ··· | 10 |
| Friedpotatoes | 36 | 23 | 23 | ··· | 5 |
| Water | 85 | 75 | 78 | ··· | 20 | | 0 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 11<br>11<br>11<br>11 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.89<br>1.00 | 0.50<br>4.99<br>49.85<br>497.92 | 0.00<br>0.01<br>0.22<br>1.18 | | | 12<br>12<br>12<br>12 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.72<br>1.00 | 0.65<br>6.49<br>64.72<br>647.08 | 0.06<br>0.24<br>2.14<br>20.84 |
| --- | --- | --- | --- | --- |
| 13<br>13<br>13<br>13 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.41<br>1.00 | 0.82<br>7.92<br>80.08<br>798.90 | 0.15<br>0.... | 1 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 11<br>11<br>11<br>11 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.89<br>1.00 | 0.50<br>4.99<br>49.85<br>497.92 | 0.00<br>0.01<br>0.22<br>1.18 | | | GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.... | 0 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 11<br>11<br>11<br>11 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.89<br>1.00 | 0.50<br>4.99<br>49.85<br>497.92 | 0.00<br>0.01<br>0.22<br>1.18 |
| 12<br>12<br>12<br>12 | 100<br>1000<br>10000<br>100000 | 0.0... | | 13<br>13<br>13<br>13 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.41<br>1.00 | 0.82<br>7.92<br>80.08<br>798.90 | 0.15<br>0.28<br>7.90<br>70.81 |
| --- | --- | --- | --- | --- |
| 14<br>14<br>14<br>14 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.15<br>1.00 | 0.96<br>9.56<br>94.81<br>945.17 | 0.16<br>1.... | 1 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 11<br>11<br>11<br>11 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.89<br>1.00 | 0.50<br>4.99<br>49.85<br>497.92 | 0.00<br>0.01<br>0.22<br>1.18 |
| 12<br>12<br>12<br>12 | 100<br>1000<br>10000<br>100000 | 0.0... | | 8<br>8<br>8<br>8<br>8<br>8<br>8<br>8<br>8<br>8 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 11.05<br>22.18<br>33.35<br>44.45<br>55.93<br>67.20<br>78.49<br>89.29<br>100.11<br>110.73 | 0.74<br>1... | 0 |
| n | k | Solved | Impossible | Unknown | Total |
| --- | --- | --- | --- | --- | --- |
| 2 | 1 | 2 | 0 | 0 | 2 |
| 2 | 2 | 2 | 0 | 0 | 2 |
| 3 | 1 | 4 | 0 | 0 | 4 | | | 3 | 2 | 9 | 2 | 0 | 11 |
| --- | --- | --- | --- | --- | --- |
| 4 | 1 | 14 | 6 | 0 | 20 |
| 5 | 1 | 28 | 34 | 6 | 68 | | 1 |
| n | k | Solved | Impossible | Unknown | Total |
| --- | --- | --- | --- | --- | --- |
| 2 | 1 | 2 | 0 | 0 | 2 |
| 2 | 2 | 2 | 0 | 0 | 2 |
| 3 | 1 | 4 | 0 | 0 | 4 | | | n= | k= | R.T.(ms) |
| --- | --- | --- |
| 1M | 1301 | 470 |
| 2.25M | 1383 | 1110 |
| 4M | 1323 | 2078 |
| 6.25M | 1261 | 4093 |
| 9M | 1256 | 7031 | | 0 |
| n | k | Solved | Impossible | Unknown | Total |
| --- | --- | --- | --- | --- | --- |
| 2 | 1 | 2 | 0 | 0 | 2 |
| 2 | 2 | 2 | 0 | 0 | 2 | | | 3 | 1 | 4 | 0 | 0 | 4 |
| --- | --- | --- | --- | --- | --- |
| 3 | 2 | 9 | 2 | 0 | 11 |
| 4 | 1 | 14 | 6 | 0 | 20 |
| 5 | 1 | 28 | 34 | 6 | 68 | | 1 |
| n | k | Solved | Impossible | Unknown | Total |
| --- | --- | --- | --- | --- | --- |
| 2 | 1 | 2 | 0 | 0 | 2 |
| 2 | 2 | 2 | 0 | 0 | 2 | | | 6.25M | 1261 | 4093 |
| --- | --- | --- |
| 9M | 1256 | 7031 | | 0 |
| State-of-the-ArtSaliencyMethods | AUC-BorjiPerformance |
| --- | --- |
| Ittietal | 0.7694 | | | SED | 0.6415 |
| --- | --- |
| SAD | 0.7521 |
| GS | 0.7597 |
| SED-OCM-GS | 0.7863 |
| SED-OCM-SAD | 0.8008 |
| SGC | 0.8205 | | 1 |
| State-of-the-ArtSaliencyMethods | AUC-BorjiPerformance |
| --- | --- |
| Ittietal | 0.7694 | | | Method | ODS | OIS | AP |
| --- | --- | --- | --- |
| SE | 0.643 | 0.680 | 0.608 |
| HED | 0.677 | 0.715 | 0.618 |
| CEDN | 0.686 | 0.718 | 0.687 |
| FCSN | 0.698 | 0.729 | 0.705 | | 0 |
| State-of-the-ArtSaliencyMethods | AUC-BorjiPerformance |
| --- | --- |
| Ittietal | 0.7694 |
| SED | 0.6415 |
| SAD | 0.7521 |
| GS | 0.7597 |
| SED-OCM-GS | 0.7863 | | | SED-OCM-SAD | 0.8008 |
| --- | --- |
| SGC | 0.8205 | | 1 |
| State-of-the-ArtSaliencyMethods | AUC-BorjiPerformance |
| --- | --- |
| Ittietal | 0.7694 |
| SED | 0.6415 |
| SAD | 0.7521 |
| GS | 0.7597 |
| SED-OCM-GS | 0.7863 | | | CEDN | 0.686 | 0.718 | 0.687 |
| --- | --- | --- | --- |
| FCSN | 0.698 | 0.729 | 0.705 | | 0 |
| n | Nodecount(M) | EdgeCount | Triangles |
| --- | --- | --- | --- |
| 8 | 65536 | 260610 | 520200 | | | 9 | 262144 | 1045506 | 2088968 |
| --- | --- | --- | --- |
| 10 | 1048576 | 4188162 | 8372232 |
| 11 | 4194304 | 16764930 | 33521672 |
| 12 | 16777216 | 67084290 | 134152200 |
| 13 | 67108864 | 268386306 | 536739848 | | 1 |
| n | Nodecount(M) | EdgeCount | Triangles |
| --- | --- | --- | --- |
| 8 | 65536 | 260610 | 520200 | | | Name | Nodes | Edges | TriangleCount | ∆ | tmax | δee∈E(G) | 3∆t |
| --- | --- | --- | --- | --- | --- | --- | --- |
| AS | 7,716 | 12,572 | 6,584 | 344 | 2,047 | 595,632 | 6,794,688 |
| Oregon | 11,492 | 23,409 | 19,894 | 537 | 3,638 | 2,347,560 | 32,049,234 |
| Enron | 36,692 | 183,831 | 727,044 | 420 | 17,744 | 75... | 0 |
| n | Nodecount(M) | EdgeCount | Triangles |
| --- | --- | --- | --- |
| 8 | 65536 | 260610 | 520200 |
| 9 | 262144 | 1045506 | 2088968 |
| 10 | 1048576 | 4188162 | 8372232 |
| 11 | 4194304 | 16764930 | 33521672 | | | 12 | 16777216 | 67084290 | 134152200 |
| --- | --- | --- | --- |
| 13 | 67108864 | 268386306 | 536739848 | | 1 |
| n | Nodecount(M) | EdgeCount | Triangles |
| --- | --- | --- | --- |
| 8 | 65536 | 260610 | 520200 |
| 9 | 262144 | 1045506 | 2088968 |
| 10 | 1048576 | 4188162 | 8372232 |
| 11 | 4194304 | 16764930 | 33521672 | | | Enron | 36,692 | 183,831 | 727,044 | 420 | 17,744 | 75,237,684 | 916,075,440 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| ca-HepPh | 12,008 | 118,489 | 3,358,499 | 450 | 39,633 | 1.8839×10 | 4.534×10 |
| AstroPh | 18,772 | 198,050 | 1,351,441 | 350 | 11,269 | 148,765,753 | 1.419×10 | | 0 |
| | Methods | N=1200 | N=2400 | N=4800 | N=9600 | N=19200 | N=38400 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| D=8 | BF-Matlab<br>BF-C<br>KDT-C<br>BF-CUDA | 0.53<br>0.55<br>0.15<br>0.02 | 1.93<br>2.30<br>0.33<br>0.10 | 8.54<br>9.73<br>0.81<br>0.38 | 37.81<br>41.35<br>2.43<br>1.71 | 154.82<br>178.32<br>6.82<... | | D=80 | BF-Matlab<br>BF-C<br>KDT-C<br>BF-CUDA | 1.81<br>2.57<br>0.98<br>0.03 | 11.72<br>10.20<br>4.29<br>0.12 | 47.56<br>42.48<br>17.22<br>0.46 | 189.25<br>177.36<br>71.43<br>2.05 | 761.09<br>708.29<br>302.44<br>9.93 | 3053.40<br>2811.92<br>1176.39<br>39.98 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| D=96 | ... | 1 |
| | Methods | N=1200 | N=2400 | N=4800 | N=9600 | N=19200 | N=38400 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| D=8 | BF-Matlab<br>BF-C<br>KDT-C<br>BF-CUDA | 0.53<br>0.55<br>0.15<br>0.02 | 1.93<br>2.30<br>0.33<br>0.10 | 8.54<br>9.73<br>0.81<br>0.38 | 37.81<br>41.35<br>2.43<br>1.71 | 154.82<br>178.32<br>6.82<... | | Method | 1500 | 5000 | 20000 | 80000 |
| --- | --- | --- | --- | --- |
| DC | (0.0553,0.2692) | (0.0286,0.1292) | (0.0144,0.0738) | (0.0072,0.0401) |
| HF | (0.0881,0.9840) | (0.0473,0.5649) | (0.0210,0.5558) | (0.0093,0.5570) |
| BD | (0.1333,1.307) | (0.0781,1.285) | (0.0445,1.482) | (0.0277,1.324) |
| (d,d)2∞ | |... | 0 |
| | Methods | N=1200 | N=2400 | N=4800 | N=9600 | N=19200 | N=38400 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| D=8 | BF-Matlab<br>BF-C<br>KDT-C<br>BF-CUDA | 0.53<br>0.55<br>0.15<br>0.02 | 1.93<br>2.30<br>0.33<br>0.10 | 8.54<br>9.73<br>0.81<br>0.38 | 37.81<br>41.35<br>2.43<br>1.71 | 154.82<br>178.32<br>6.82<... | | D=16 | BF-Matlab<br>BF-C<br>KDT-C<br>BF-CUDA | 0.56<br>0.64<br>0.28<br>0.02 | 2.34<br>2.70<br>1.06<br>0.10 | 9.62<br>11.31<br>5.04<br>0.38 | 53.64<br>47.73<br>23.97<br>1.78 | 222.81<br>205.51<br>91.33<br>7.98 | 930.93<br>871.94<br>319.01<br>31.31 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| D=32 | BF-Matlab<... | 1 |
| | Methods | N=1200 | N=2400 | N=4800 | N=9600 | N=19200 | N=38400 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| D=8 | BF-Matlab<br>BF-C<br>KDT-C<br>BF-CUDA | 0.53<br>0.55<br>0.15<br>0.02 | 1.93<br>2.30<br>0.33<br>0.10 | 8.54<br>9.73<br>0.81<br>0.38 | 37.81<br>41.35<br>2.43<br>1.71 | 154.82<br>178.32<br>6.82<... | | (d,d)2∞ | | | | |
| --- | --- | --- | --- | --- |
| DC | 0.096 | 0.584 | 3.11 | 24.5 |
| HF | 0.987 | 3.14 | 12.0 | 47.3 |
| BD | 74.2 | 227 | 940 | 4204 |
| timing(sec) | | | | | | 0 |
| Metric | Noise | MagicPointLMagicPointSFASTHarrisShi |
| --- | --- | --- |
| mAP | nonoise | 0.9790.9800.4050.6780.686 |
| mAP | noise | 0.9710.9390.0610.2130.157 | | | MLE | nonoise | 0.8600.9221.6561.2451.188 |
| --- | --- | --- |
| MLE | noise | 1.0121.0781.7661.4091.383 | | 1 |
| Metric | Noise | MagicPointLMagicPointSFASTHarrisShi |
| --- | --- | --- |
| mAP | nonoise | 0.9790.9800.4050.6780.686 |
| mAP | noise | 0.9710.9390.0610.2130.157 | | | Metric | Noise | Resolution | MagicPointLMagicPointSFASTHarrisShi |
| --- | --- | --- | --- |
| mAP | no | 160x120 | 0.8880.8500.6420.8030.674 |
| mAP | yes | 160x120 | 0.8110.7300.0660.1660.132 |
| MLE | no | 160x120 | 1.3651.3911.9081.3691.551 |
| MLE | yes | 160x120 | 1.4701.5372.2361.7751.858 |
| R | no | 160x120... | 0 |
| Metric | Noise | MagicPointLMagicPointSFASTHarrisShi |
| --- | --- | --- |
| mAP | nonoise | 0.9790.9800.4050.6780.686 |
| mAP | noise | 0.9710.9390.0610.2130.157 | | | MLE | nonoise | 0.8600.9221.6561.2451.188 |
| --- | --- | --- |
| MLE | noise | 1.0121.0781.7661.4091.383 | | 1 |
| Metric | Noise | MagicPointLMagicPointSFASTHarrisShi |
| --- | --- | --- |
| mAP | nonoise | 0.9790.9800.4050.6780.686 |
| mAP | noise | 0.9710.9390.0610.2130.157 | | | MLE | no | 160x120 | 1.3651.3911.9081.3691.551 |
| --- | --- | --- | --- |
| MLE | yes | 160x120 | 1.4701.5372.2361.7751.858 |
| R | no | 160x120 | 0.9700.9290.8000.9290.852 |
| R | yes | 160x120 | 0.8110.7110.1410.1360.148 |
| mAP | no | 320x240 | 0.8920.8160.4050.6780.686 |
| mAP | yes | 320x240 | 0.8460.6870.0180.... | 0 |
| Samplingstrategy | Time |
| --- | --- |
| Simplesampling,withscaling(10000particles) | 0.046s |
| Simplesampling,noscaling(10000particles) | 0.028s |
| GMMsampling(10000particles) | 2.947s | | | MKF(30mixturecomponents) | 0.021s |
| --- | --- |
| MKF,fixedtracks(30mixturetrajectories) | 0.015s | | 1 |
| Samplingstrategy | Time |
| --- | --- |
| Simplesampling,withscaling(10000particles) | 0.046s |
| Simplesampling,noscaling(10000particles) | 0.028s |
| GMMsampling(10000particles) | 2.947s | | | Sampling | Pointsn. | Accuracy |
| --- | --- | --- |
| 1s | 13345 | 0.9732 |
| 10s | 1352 | 0.9415 |
| 30s | 462 | 0.9545 |
| 90s | 165 | 0.9939 |
| 120s | 129 | 0.9689 | | 0 |
| Samplingstrategy | Time |
| --- | --- |
| Simplesampling,withscaling(10000particles) | 0.046s |
| Simplesampling,noscaling(10000particles) | 0.028s |
| GMMsampling(10000particles) | 2.947s | | | MKF(30mixturecomponents) | 0.021s |
| --- | --- |
| MKF,fixedtracks(30mixturetrajectories) | 0.015s | | 1 |
| Samplingstrategy | Time |
| --- | --- |
| Simplesampling,withscaling(10000particles) | 0.046s |
| Simplesampling,noscaling(10000particles) | 0.028s |
| GMMsampling(10000particles) | 2.947s | | | 10s | 1352 | 0.9415 |
| --- | --- | --- |
| 30s | 462 | 0.9545 |
| 90s | 165 | 0.9939 |
| 120s | 129 | 0.9689 | | 0 |
| Cluster | Stations | Trips | | |
| --- | --- | --- | --- | --- |
| within | out | in | | |
| Central/East(1) | 408 | 760,404 | 112,263 | 118,146 | | | West(2) | 190 | 184,714 | 80,457 | 82,332 |
| --- | --- | --- | --- | --- |
| RegentsPark(3) | 71 | 48,259 | 75,618 | 71,990 |
| HydePark(4) | 26 | 80,354 | 63,617 | 60,289 |
| NottingHill(5) | 35 | 17,481 | 30,443 | 29,084 |
| CanaryWharf(6) | 20 | 9,060 | 7,181 | 7,738 | | 1 |
| Cluster | Stations | Trips | | |
| --- | --- | --- | --- | --- |
| within | out | in | | |
| Central/East(1) | 408 | 760,404 | 112,263 | 118,146 | | | City | N | K | NGC | C | Cr | d | dr | Q | Qr |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Atlanta | 13,011 | 46,756 | 11,476 | 0.16 | 0.0006 | 4.6 | 4.6 | 0.53 | 0.17 |
| Boston | 10,478 | 41,505 | 8,816 | 0.17 | 0.0010 | 4.3 | 4.0 | 0.45 | 0.15 |
| Chicago | 19,931 | 84,778 | 17,287 | 0.16 | 0.... | 0 |
| Cluster | Stations | Trips | | |
| --- | --- | --- | --- | --- |
| within | out | in | | |
| Central/East(1) | 408 | 760,404 | 112,263 | 118,146 |
| West(2) | 190 | 184,714 | 80,457 | 82,332 |
| RegentsPark(3) | 71 | 48,259 | 75,618 | 71,990 | | | HydePark(4) | 26 | 80,354 | 63,617 | 60,289 |
| --- | --- | --- | --- | --- |
| NottingHill(5) | 35 | 17,481 | 30,443 | 29,084 |
| CanaryWharf(6) | 20 | 9,060 | 7,181 | 7,738 | | 1 |
| Cluster | Stations | Trips | | |
| --- | --- | --- | --- | --- |
| within | out | in | | |
| Central/East(1) | 408 | 760,404 | 112,263 | 118,146 |
| West(2) | 190 | 184,714 | 80,457 | 82,332 |
| RegentsPark(3) | 71 | 48,259 | 75,618 | 71,990 | | | Boston | 10,478 | 41,505 | 8,816 | 0.17 | 0.0010 | 4.3 | 4.0 | 0.45 | 0.15 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Chicago | 19,931 | 84,778 | 17,287 | 0.16 | 0.0004 | 4.6 | 4.9 | 0.47 | 0.14 |
| Minneapolis | 6,499 | 30,640 | 5,914 | 0.18 | 0.0016 | 4.4 | 4.2 | 0.41 | 0.12 |
| Seattle | 7,4... | 0 |
| Actions | SVM<br>-SW | RNN<br>-SW | CA<br>-RNN | JCR<br>-RNN |
| --- | --- | --- | --- | --- |
| drinking | 0.146 | 0.441 | 0.584 | 0.574 |
| eating | 0.465 | 0.550 | 0.558 | 0.523 | | | writing | 0.645 | 0.859 | 0.749 | 0.822 |
| --- | --- | --- | --- | --- |
| openingcupboard | 0.308 | 0.321 | 0.490 | 0.495 |
| washinghands | 0.562 | 0.668 | 0.672 | 0.718 |
| openingmicrowave | 0.607 | 0.665 | 0.468 | 0.703 |
| sweeping | 0.461 | 0.590 | 0.597 | 0.643 |
| gargling | 0.437 | 0.550 | 0.579 | 0.623 |
... | 1 |
| Actions | SVM<br>-SW | RNN<br>-SW | CA<br>-RNN | JCR<br>-RNN |
| --- | --- | --- | --- | --- |
| drinking | 0.146 | 0.441 | 0.584 | 0.574 |
| eating | 0.465 | 0.550 | 0.558 | 0.523 | | | Actions | SVM-SW | RNN-SW | CA-RNN | JCR-RNN | RF | RF+T | RF+ST |
| --- | --- | --- | --- | --- | --- | --- | --- |
| drinking<br>eating<br>writing<br>openingcupboard<br>washinghands<br>openingmicrowave<br>sweeping<br>gargling<br>throwingtrash<br>wiping | 0.146<br>0.465<br>0.645<br>0.308<br>0.562<br>0.607<br>0.461<b... | 0 |
| Actions | SVM<br>-SW | RNN<br>-SW | CA<br>-RNN | JCR<br>-RNN |
| --- | --- | --- | --- | --- |
| drinking | 0.146 | 0.441 | 0.584 | 0.574 |
| eating | 0.465 | 0.550 | 0.558 | 0.523 |
| writing | 0.645 | 0.859 | 0.749 | 0.822 |
| openingcupboard | 0.308 | 0.321 | 0.490 | 0.495 |
| washinghands | 0.562 | 0.668 | 0.672 ... | | sweeping | 0.461 | 0.590 | 0.597 | 0.643 |
| --- | --- | --- | --- | --- |
| gargling | 0.437 | 0.550 | 0.579 | 0.623 |
| throwingtrash | 0.554 | 0.674 | 0.430 | 0.459 |
| wiping | 0.857 | 0.747 | 0.761 | 0.780 |
| average | 0.540 | 0.600 | 0.596 | 0.653 | | 1 |
| Actions | SVM<br>-SW | RNN<br>-SW | CA<br>-RNN | JCR<br>-RNN |
| --- | --- | --- | --- | --- |
| drinking | 0.146 | 0.441 | 0.584 | 0.574 |
| eating | 0.465 | 0.550 | 0.558 | 0.523 |
| writing | 0.645 | 0.859 | 0.749 | 0.822 |
| openingcupboard | 0.308 | 0.321 | 0.490 | 0.495 |
| washinghands | 0.562 | 0.668 | 0.672 ... | | TestingTimeRatio | 1.05 | 3.14 | − | 2.60 | 1.60 | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| SL−<br>EL− | 0.316<br>0.325 | 0.366<br>0.376 | 0.378<br>0.382 | 0.418<br>0.443 | 0.320<br>0.342 | 0.356<br>0.367 | 0.445<br>0.432 | | 0 |
| | Accuracy(Unsupervised) | Accuracy(Supervised) |
| --- | --- | --- |
| CNN-H1 | 98.12±0.24 | 98.43±0.20 | | | CNN-H2 | 96.47±0.44 | 97.67±0.28 |
| --- | --- | --- |
| CNN-P1 | 96.83±0.26 | 97.30±0.22 |
| CNN-P2 | 97.25±0.31 | 98.00±0.24 |
| CNN-P3 | 96.70±0.25 | 97.82±0.16 |
| CNN-P4 | 96.17±0.31 | 96.93±0.21 |
| CNN-P5 | 96.05±0.27 | 97.23±0.20 |
| CNN-P6 | 95.58±0.17 | 96.72±0.21 | | 1 |
| | Accuracy(Unsupervised) | Accuracy(Supervised) |
| --- | --- | --- |
| CNN-H1 | 98.12±0.24 | 98.43±0.20 | | | Network | Precision | Recall | F1-Score |
| --- | --- | --- | --- |
| AlexNet | 0.28 | 0.67 | 0.40 |
| RAN-CNN-FC6-3L | 0.77 | 0.82 | 0.79 |
| RAN-CNN-FC6-5L | 0.82 | 0.81 | 0.81 |
| RAN-CNN-FC7-5L | 0.79 | 0.81 | 0.80 |
| RAN-CNN-FC6-5L-D | 0.81 | 0.83 | 0.82 |
| RAN-LSTM-1L | 0.74 | 0.82 | 0.78 |
| RAN-LSTM-2L | 0.... | 0 |
| | Accuracy(Unsupervised) | Accuracy(Supervised) |
| --- | --- | --- |
| CNN-H1 | 98.12±0.24 | 98.43±0.20 |
| CNN-H2 | 96.47±0.44 | 97.67±0.28 |
| CNN-P1 | 96.83±0.26 | 97.30±0.22 | | | CNN-P2 | 97.25±0.31 | 98.00±0.24 |
| --- | --- | --- |
| CNN-P3 | 96.70±0.25 | 97.82±0.16 |
| CNN-P4 | 96.17±0.31 | 96.93±0.21 |
| CNN-P5 | 96.05±0.27 | 97.23±0.20 |
| CNN-P6 | 95.58±0.17 | 96.72±0.21 | | 1 |
| | Accuracy(Unsupervised) | Accuracy(Supervised) |
| --- | --- | --- |
| CNN-H1 | 98.12±0.24 | 98.43±0.20 |
| CNN-H2 | 96.47±0.44 | 97.67±0.28 |
| CNN-P1 | 96.83±0.26 | 97.30±0.22 | | | RAN-LSTM-1L | 0.74 | 0.82 | 0.78 |
| --- | --- | --- | --- |
| RAN-LSTM-2L | 0.85 | 0.81 | 0.83 | | 0 |
| | Training | Testing | Validation |
| --- | --- | --- | --- |
| ModelI | 3588 | 1184 | 1189 | | | ModelII | 5259 | 1763 | 1746 |
| --- | --- | --- | --- |
| ModelIII | 3980 | 1368 | 1350 |
| ModelIV | 2212 | 733 | 742 |
| Total | 15039 | 5048 | 5027 | | 1 |
| | Training | Testing | Validation |
| --- | --- | --- | --- |
| ModelI | 3588 | 1184 | 1189 | | | | Train | Validation | Test |
| --- | --- | --- | --- |
| PA | 70,875 | 10,078 | 20,426 |
| AP | 168,525 | 24,566 | 47,689 |
| Lateral | 81,379 | 11,519 | 23,125 |
| Total | 320,779 | 46,163 | 91,240 | | 0 |
| | Training | Testing | Validation |
| --- | --- | --- | --- |
| ModelI | 3588 | 1184 | 1189 |
| ModelII | 5259 | 1763 | 1746 | | | ModelIII | 3980 | 1368 | 1350 |
| --- | --- | --- | --- |
| ModelIV | 2212 | 733 | 742 |
| Total | 15039 | 5048 | 5027 | | 1 |
| | Training | Testing | Validation |
| --- | --- | --- | --- |
| ModelI | 3588 | 1184 | 1189 |
| ModelII | 5259 | 1763 | 1746 | | | AP | 168,525 | 24,566 | 47,689 |
| --- | --- | --- | --- |
| Lateral | 81,379 | 11,519 | 23,125 |
| Total | 320,779 | 46,163 | 91,240 | | 0 |
| h | Averagejumpfactorwithvaryingγ | | | | |
| --- | --- | --- | --- | --- | --- |
| γ=0 | γ=3 | γ=4 | γ=5 | γ=6 | |
| 10 | 2.2 | 1.82 | 1.77 | 1.77 | 1.77 |
| 50 | 5.16 | 3.86 | 2.95 | 2.11 | 1.96 | | | 100 | 8.03 | 5.81 | 4.14 | 2.75 | 1.97 |
| --- | --- | --- | --- | --- | --- |
| 500 | 29.11 | 20.47 | 14.27 | 8.02 | 2.43 |
| 1000 | 52.47 | 37.46 | 25.66 | 13.87 | 3.11 | | 1 |
| h | Averagejumpfactorwithvaryingγ | | | | |
| --- | --- | --- | --- | --- | --- |
| γ=0 | γ=3 | γ=4 | γ=5 | γ=6 | |
| 10 | 2.2 | 1.82 | 1.77 | 1.77 | 1.77 |
| 50 | 5.16 | 3.86 | 2.95 | 2.11 | 1.96 | | | (a) | (b) | (c) | (d) | (e) | (f) | (g) | (h) | (i) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 5.05 | 6.15 | 4.61 | 4.10 | 5.27 | 2.51 | 4.51 | 4.50 | 2.81 |
| 6.01 | 2.32 | 2.53 | – | 2.26 | 2.46 | 2.93 | 2.04 | 1.62 |
| 7.09 | 2.54 | 2.49 | – | 1.93 | 2.61 | 2.36 | 1.89 | 1.57 |
| 10.84 | 6.60 | 11... | 0 |
| h | Averagejumpfactorwithvaryingγ | | | |
| --- | --- | --- | --- | --- |
| γ=0 | γ=3 | γ=4 | γ=5 | γ=6 | | | 10 | 2.2 | 1.82 | 1.77 | 1.77 | 1.77 |
| --- | --- | --- | --- | --- | --- |
| 50 | 5.16 | 3.86 | 2.95 | 2.11 | 1.96 |
| 100 | 8.03 | 5.81 | 4.14 | 2.75 | 1.97 |
| 500 | 29.11 | 20.47 | 14.27 | 8.02 | 2.43 |
| 1000 | 52.47 | 37.46 | 25.66 | 13.87 | 3.11 | | 1 |
| h | Averagejumpfactorwithvaryingγ | | | |
| --- | --- | --- | --- | --- |
| γ=0 | γ=3 | γ=4 | γ=5 | γ=6 | | | 6.01 | 2.32 | 2.53 | – | 2.26 | 2.46 | 2.93 | 2.04 | 1.62 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 7.09 | 2.54 | 2.49 | – | 1.93 | 2.61 | 2.36 | 1.89 | 1.57 |
| 10.84 | 6.60 | 11.79 | – | 8.91 | 11.71 | 7.93 | 9.47 | 3.50 | | 0 |
| | ObjectDetection(AP) | Orientation(AOS) | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Methods | Easy | Moderate | Hard | Easy | Moderate | Hard |
| Car | | | | | | |
| RPN+ | 82.91 | 77.83 | 66.25 | N/A | N/A | N/A |
| OurRPN+ | 95.14 | 85.20 | 72.12 | N/A | N/A | N/A |
| Oursw/oPose | 94.66 | 8... | | OurRPN+ | 85.96 | 68.55 | 62.55 | N/A | N/A | N/A |
| --- | --- | --- | --- | --- | --- | --- |
| Oursw/oPose | 83.22 | 67.61 | 62.03 | N/A | N/A | N/A |
| Oursw/oExtra | 84.86 | 68.87 | 63.09 | 74.05 | 59.06 | 54.05 |
| OursFull | 86.43 | 69.95 | 64.03 | 73.91 | 58.91 | 53.79 |
| Cyclist | | | | | | |
| RPN+ |... | 1 |
| | ObjectDetection(AP) | Orientation(AOS) | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Methods | Easy | Moderate | Hard | Easy | Moderate | Hard |
| Car | | | | | | |
| RPN+ | 82.91 | 77.83 | 66.25 | N/A | N/A | N/A |
| OurRPN+ | 95.14 | 85.20 | 72.12 | N/A | N/A | N/A |
| Oursw/oPose | 94.66 | 8... | | Methods | Easy | Moderate | Hard |
| --- | --- | --- | --- |
| Car | | | |
| SelectiveSearch | 58.17 | 42.12 | 37.62 |
| EdgeBoxes | 81.40 | 61.84 | 55.68 |
| RPN | 98.84 | 97.37 | 95.31 |
| Ours | 99.27 | 96.28 | 93.14 |
| Pedestrian | | | |
| SelectiveSearch | 68.95 | 57.65 | 52.57 |
| EdgeBoxes | 86.15 | 71.... | 0 |
| | ObjectDetection(AP) | Orientation(AOS) | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Methods | Easy | Moderate | Hard | Easy | Moderate | Hard |
| Car | | | | | | |
| RPN+ | 82.91 | 77.83 | 66.25 | N/A | N/A | N/A |
| OurRPN+ | 95.14 | 85.20 | 72.12 | N/A | N/A | N/A |
| Oursw/oPose | 94.66 | 8... | | Oursw/oPose | 83.22 | 67.61 | 62.03 | N/A | N/A | N/A |
| --- | --- | --- | --- | --- | --- | --- |
| Oursw/oExtra | 84.86 | 68.87 | 63.09 | 74.05 | 59.06 | 54.05 |
| OursFull | 86.43 | 69.95 | 64.03 | 73.91 | 58.91 | 53.79 |
| Cyclist | | | | | | |
| RPN+ | 56.36 | 46.36 | 42.77 | N/A | N/A | N/A |
| OurRPN+ |... | 1 |
| | ObjectDetection(AP) | Orientation(AOS) | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Methods | Easy | Moderate | Hard | Easy | Moderate | Hard |
| Car | | | | | | |
| RPN+ | 82.91 | 77.83 | 66.25 | N/A | N/A | N/A |
| OurRPN+ | 95.14 | 85.20 | 72.12 | N/A | N/A | N/A |
| Oursw/oPose | 94.66 | 8... | | SelectiveSearch | 68.95 | 57.65 | 52.57 |
| --- | --- | --- | --- |
| EdgeBoxes | 86.15 | 71.88 | 65.39 |
| RPN | 98.88 | 91.69 | 88.64 |
| Ours | 99.44 | 93.46 | 91.02 |
| Cyclist | | | |
| SelectiveSearch | 57.05 | 49.59 | 49.44 |
| EdgeBoxes | 56.11 | 46.52 | 45.72 |
| RPN | 96.55 | 91.80 | 89.41 |
| Ours | 99.... | 0 |
| | Top10Features |
| --- | --- |
| 1 | Location(State) |
| 2 | NumberofSpecialCharacters |
| 3 | LongestCommonSubstring |
| 4 | NumberofUniqueTokens |
| 5 | TimeDifference |
| 6 | IfPostedonSameDay | | | 7 | PresenceofEthnicity |
| --- | --- |
| 8 | PresenceofRate |
| 9 | PresenceofRestrictions |
| 10 | PresenceofNames | | 1 |
| | Top10Features |
| --- | --- |
| 1 | Location(State) |
| 2 | NumberofSpecialCharacters |
| 3 | LongestCommonSubstring |
| 4 | NumberofUniqueTokens |
| 5 | TimeDifference |
| 6 | IfPostedonSameDay | | | | Individualusersgroup |
| --- | --- |
| Totalnumberoftweets | 119,376 |
| Totalnumberofuniqueaccounts | 80,537 |
| Totalnumberoftokens | 1,837,304 |
| Averagenumberoftokenspertweet | 15.391 |
| Totalnumberofuniquetokens | 103,089 |
| Averagenumberofuniquetokenspertweet | 0.864 |
| Uniquetokens:tokensratio | 0.056 |... | 0 |
| | Top10Features |
| --- | --- |
| 1 | Location(State) | | | 2 | NumberofSpecialCharacters |
| --- | --- |
| 3 | LongestCommonSubstring |
| 4 | NumberofUniqueTokens |
| 5 | TimeDifference |
| 6 | IfPostedonSameDay |
| 7 | PresenceofEthnicity |
| 8 | PresenceofRate |
| 9 | PresenceofRestrictions |
| 10 | PresenceofNames | | 1 |
| | Top10Features |
| --- | --- |
| 1 | Location(State) | | | Totalnumberoftokens | 1,837,304 |
| --- | --- |
| Averagenumberoftokenspertweet | 15.391 |
| Totalnumberofuniquetokens | 103,089 |
| Averagenumberofuniquetokenspertweet | 0.864 |
| Uniquetokens:tokensratio | 0.056 |
| Numberofhapaxlegomena | 69,542 |
| Averagenumberofhapaxlegomenapertweet | 0.583 | | 0 |
| Variable | Description |
| --- | --- |
| pi | numberoftweetsmadebyuseri |
| fi | numberoffollowersofi | | | ri | numberofretweetsofi’spostsbyfollowers |
| --- | --- |
| mi | numbermentionsofibyfollowers |
| P<br>f | probabilityofgainingfollowers |
| P<br>f | probabilityoflosingfollowers | | 1 |
| Variable | Description |
| --- | --- |
| pi | numberoftweetsmadebyuseri |
| fi | numberoffollowersofi | | | Variable | Description |
| --- | --- |
| j | theidentifieroftheneighbor |
| tj | theageoftheneighbor |
| aj | theattributevalueoftheneighbor |
| rj | therandomvalueoftheneighbor | | 0 |
| Variable | Description |
| --- | --- |
| pi | numberoftweetsmadebyuseri |
| fi | numberoffollowersofi |
| ri | numberofretweetsofi’spostsbyfollowers |
| mi | numbermentionsofibyfollowers | | | P<br>f | probabilityofgainingfollowers |
| --- | --- |
| P<br>f | probabilityoflosingfollowers | | 1 |
| Variable | Description |
| --- | --- |
| pi | numberoftweetsmadebyuseri |
| fi | numberoffollowersofi |
| ri | numberofretweetsofi’spostsbyfollowers |
| mi | numbermentionsofibyfollowers | | | tj | theageoftheneighbor |
| --- | --- |
| aj | theattributevalueoftheneighbor |
| rj | therandomvalueoftheneighbor | | 0 |
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