premise string | hypothesis string | label int64 |
|---|---|---|
| Labels | Positive | Negative |
| --- | --- | --- |
| Wound | 615 | 720 |
| Infection(SSI) | 355 | 980 |
| GranulationTissue | 449 | 886 |
| FibrinousExudate | 398 | 937 |
| OpenWound | 631 | 704 |
| Drainage | 448 | 887 | | | SteriStrips | 129 | 1206 |
| --- | --- | --- |
| Staples | 98 | 1237 |
| Sutures | 160 | 1175 | | 1 |
| Labels | Positive | Negative |
| --- | --- | --- |
| Wound | 615 | 720 |
| Infection(SSI) | 355 | 980 |
| GranulationTissue | 449 | 886 |
| FibrinousExudate | 398 | 937 |
| OpenWound | 631 | 704 |
| Drainage | 448 | 887 | | | Word1 | Word2 | Similarity |
| --- | --- | --- |
| large | NEGEXenlarged | -0.245 |
| hemorrhage | NEGEXQUALhemorrhage | -0.074 |
| hemorrhage | NEGEXQUALintracranialhemorrhage | -0.245 |
| infarction | NEGEXQUALinfarction | -0.070 |
| largeterritoryinfarction | NEGEXQUALlargeterritoryinfarction | -0.157 |
| midlineshift | NEGEXQUALmidlineshift | -0.206 |
| abnormalities | NEGEXQUALabnormalities | -0.283 |
| masseffect | NEGEXQUALmasseffect | -0.170 | | 0 |
| Labels | Positive | Negative |
| --- | --- | --- |
| Wound | 615 | 720 |
| Infection(SSI) | 355 | 980 |
| GranulationTissue | 449 | 886 |
| FibrinousExudate | 398 | 937 |
| OpenWound | 631 | 704 |
| Drainage | 448 | 887 |
| SteriStrips | 129 | 1206 | | | Staples | 98 | 1237 |
| --- | --- | --- |
| Sutures | 160 | 1175 | | 1 |
| Labels | Positive | Negative |
| --- | --- | --- |
| Wound | 615 | 720 |
| Infection(SSI) | 355 | 980 |
| GranulationTissue | 449 | 886 |
| FibrinousExudate | 398 | 937 |
| OpenWound | 631 | 704 |
| Drainage | 448 | 887 |
| SteriStrips | 129 | 1206 | | | abnormalities | NEGEXQUALabnormalities | -0.283 |
| --- | --- | --- |
| masseffect | NEGEXQUALmasseffect | -0.170 | | 0 |
| Network | Asymmetric,<br>per-layer | Symmetric,<br>per-channel | Asymmetric,<br>per-channel | Activation<br>Only | Floating<br>Point |
| --- | --- | --- | --- | --- | --- |
| Mobilenet-v11224 | 0.001 | 0.591 | 0.703 | 0.708 | 0.709 |
| Mobilenet-v21224 | 0.001 | 0.698 | 0.697 | 0.7 | 0.719 |
| Nasnet-Mobile | 0.722 | 0.721 | 0.74 | 0.74 | 0.74 |
| Mobilenet-v21.4224 | 0.004 | 0.74 | 0.74 | 0.742 | 0.749 |
| Inception-v3 | 0.78 | 0.78 | 0.78 | 0.78 | 0.78 |
| Resnet-v150 | 0.75 | 0.751 | 0.751 | 0.751 | 0.752 |
| Resnet-v250 | 0.75 | 0.75 | 0.75 | 0.75 | 0.756 | | | Resnet-v1152 | 0.766 | 0.762 | 0.767 | 0.761 | 0.768 |
| --- | --- | --- | --- | --- | --- |
| Resnet-v2152 | 0.761 | 0.76 | 0.76 | 0.76 | 0.778 | | 1 |
| Network | Asymmetric,<br>per-layer | Symmetric,<br>per-channel | Asymmetric,<br>per-channel | Activation<br>Only | Floating<br>Point |
| --- | --- | --- | --- | --- | --- |
| Mobilenet-v11224 | 0.001 | 0.591 | 0.703 | 0.708 | 0.709 |
| Mobilenet-v21224 | 0.001 | 0.698 | 0.697 | 0.7 | 0.719 |
| Nasnet-Mobile | 0.722 | 0.721 | 0.74 | 0.74 | 0.74 |
| Mobilenet-v21.4224 | 0.004 | 0.74 | 0.74 | 0.742 | 0.749 |
| Inception-v3 | 0.78 | 0.78 | 0.78 | 0.78 | 0.78 |
| Resnet-v150 | 0.75 | 0.751 | 0.751 | 0.751 | 0.752 |
| Resnet-v250 | 0.75 | 0.75 | 0.75 | 0.75 | 0.756 | | | Network | Asymmetric,<br>per-layer | Symmetric,<br>per-channel | Asymmetric,<br>per-channel | Floating<br>Point |
| --- | --- | --- | --- | --- |
| Mobilenetv11224 | 0.001 | 0.591 | 0.704 | 0.709 |
| Mobilenetv21224 | 0.001 | 0.698 | 0.698 | 0.719 |
| NasnetMobile | 0.722 | 0.721 | 0.74 | 0.74 |
| Mobilenetv21.4224 | 0.004 | 0.74 | 0.74 | 0.749 |
| Inceptionv3 | 0.78 | 0.78 | 0.78 | 0.78 |
| Resnetv150 | 0.75 | 0.751 | 0.752 | 0.752 |
| Resnetv250 | 0.75 | 0.75 | 0.75 | 0.756 |
| Resnetv1152 | 0.766 | 0.763 | 0.762 | 0.768 |
| Resnetv2152 | 0.761 | 0.76 | 0.77 | 0.778 | | 0 |
| Network | Asymmetric,<br>per-layer | Symmetric,<br>per-channel | Asymmetric,<br>per-channel | Activation<br>Only | Floating<br>Point |
| --- | --- | --- | --- | --- | --- |
| Mobilenet-v11224 | 0.001 | 0.591 | 0.703 | 0.708 | 0.709 |
| Mobilenet-v21224 | 0.001 | 0.698 | 0.697 | 0.7 | 0.719 |
| Nasnet-Mobile | 0.722 | 0.721 | 0.74 | 0.74 | 0.74 | | | Mobilenet-v21.4224 | 0.004 | 0.74 | 0.74 | 0.742 | 0.749 |
| --- | --- | --- | --- | --- | --- |
| Inception-v3 | 0.78 | 0.78 | 0.78 | 0.78 | 0.78 |
| Resnet-v150 | 0.75 | 0.751 | 0.751 | 0.751 | 0.752 |
| Resnet-v250 | 0.75 | 0.75 | 0.75 | 0.75 | 0.756 |
| Resnet-v1152 | 0.766 | 0.762 | 0.767 | 0.761 | 0.768 |
| Resnet-v2152 | 0.761 | 0.76 | 0.76 | 0.76 | 0.778 | | 1 |
| Network | Asymmetric,<br>per-layer | Symmetric,<br>per-channel | Asymmetric,<br>per-channel | Activation<br>Only | Floating<br>Point |
| --- | --- | --- | --- | --- | --- |
| Mobilenet-v11224 | 0.001 | 0.591 | 0.703 | 0.708 | 0.709 |
| Mobilenet-v21224 | 0.001 | 0.698 | 0.697 | 0.7 | 0.719 |
| Nasnet-Mobile | 0.722 | 0.721 | 0.74 | 0.74 | 0.74 | | | NasnetMobile | 0.722 | 0.721 | 0.74 | 0.74 |
| --- | --- | --- | --- | --- |
| Mobilenetv21.4224 | 0.004 | 0.74 | 0.74 | 0.749 |
| Inceptionv3 | 0.78 | 0.78 | 0.78 | 0.78 |
| Resnetv150 | 0.75 | 0.751 | 0.752 | 0.752 |
| Resnetv250 | 0.75 | 0.75 | 0.75 | 0.756 |
| Resnetv1152 | 0.766 | 0.763 | 0.762 | 0.768 |
| Resnetv2152 | 0.761 | 0.76 | 0.77 | 0.778 | | 0 |
| | | | Qine | |
| --- | --- | --- | --- | --- |
| problem | ratio | Rsolver | 2B | 2B+ |
| Circle | 0.98<br>0.99<br>0.999 | 55.67<br>169.51<br>− | 0.90<br>2.32<br>69.18 | 1.03<br>2.22<br>31.55 |
| PathPoint | 0.6<br>0.65<br>0.7 | 122.72<br>334.34<br>− | 0.01<br>0.01<br>0.02 | 0.01<br>0.02<br>0.03 | | | Parabola | 0.96<br>0.97<br>0.98 | 48.33<br>130.30<br>− | 1.47<br>2.74<br>8.77 | 1.36<br>1.92<br>6.59 |
| --- | --- | --- | --- | --- |
| Robot | 0.98<br>0.99<br>0.999 | 10.34<br>26.74<br>− | 0.06<br>0.14<br>5.37 | 0.08<br>0.18<br>4.08 |
| Satellite | 0.5<br>0.55<br>0.6 | 303.30<br>−<br>− | 71.36<br>168.32<br>227.09 | 114.33<br>268.36<br>368.90 |
| Robust1 | 0.999<br>0.9999<br>0.99999 | 1.10<br>7.16<br>76.25 | 0.01<br>0.04<br>0.10 | 0.00<br>0.00<br>0.00 |
| Robust4 | 0.5<br>0.55<br>0.6 | −<br>−<br>− | −<br>−<br>− | 0.00<br>0.01<br>0.01 |
| Robust5 | 0.7<br>0.75<br>0.8 | 75.35<br>80.62<br>− | 0.00<br>0.00<br>0.01 | 0.00<br>0.00<br>0.00 |
| Robust6 | 0.7<br>0.75<br>0.8 | 59.98<br>224.33<br>− | 0.02<br>0.05<br>0.09 | 0.00<br>0.00<br>0.00 | | 1 |
| | | | Qine | |
| --- | --- | --- | --- | --- |
| problem | ratio | Rsolver | 2B | 2B+ |
| Circle | 0.98<br>0.99<br>0.999 | 55.67<br>169.51<br>− | 0.90<br>2.32<br>69.18 | 1.03<br>2.22<br>31.55 |
| PathPoint | 0.6<br>0.65<br>0.7 | 122.72<br>334.34<br>− | 0.01<br>0.01<br>0.02 | 0.01<br>0.02<br>0.03 | | | Depth | Para | C-10 |
| --- | --- | --- |
| - | | 7.25 |
| 110 | 1.7M | 6.61 |
| 28 | 36.5M | 4.17 |
| 1001 | 10.2M | 4.62 |
| 40<br>100<br>100<br>190 | 1.0M<br>7.0M<br>27.2M<br>25.6M | 5.24<br>4.10<br>3.74<br>3.46 |
| -<br>- | -<br>11.2M | 7.32<br>6.92 |
| 15<br>20<br>39<br>39 | 4.2M<br>2.5M<br>7.1M<br>37.4M | 5.50<br>6.01<br>4.47<br>3.65 |
| 25<br>37<br>19<br>22 | -<br>-<br>6.1M<br>39.8M | 3.60<br>3.80<br>4.38<br>3.54 | | 0 |
| | | | Qine | |
| --- | --- | --- | --- | --- |
| problem | ratio | Rsolver | 2B | 2B+ |
| Circle | 0.98<br>0.99<br>0.999 | 55.67<br>169.51<br>− | 0.90<br>2.32<br>69.18 | 1.03<br>2.22<br>31.55 |
| PathPoint | 0.6<br>0.65<br>0.7 | 122.72<br>334.34<br>− | 0.01<br>0.01<br>0.02 | 0.01<br>0.02<br>0.03 |
| Parabola | 0.96<br>0.97<br>0.98 | 48.33<br>130.30<br>− | 1.47<br>2.74<br>8.77 | 1.36<br>1.92<br>6.59 |
| Robot | 0.98<br>0.99<br>0.999 | 10.34<br>26.74<br>− | 0.06<br>0.14<br>5.37 | 0.08<br>0.18<br>4.08 | | | Satellite | 0.5<br>0.55<br>0.6 | 303.30<br>−<br>− | 71.36<br>168.32<br>227.09 | 114.33<br>268.36<br>368.90 |
| --- | --- | --- | --- | --- |
| Robust1 | 0.999<br>0.9999<br>0.99999 | 1.10<br>7.16<br>76.25 | 0.01<br>0.04<br>0.10 | 0.00<br>0.00<br>0.00 |
| Robust4 | 0.5<br>0.55<br>0.6 | −<br>−<br>− | −<br>−<br>− | 0.00<br>0.01<br>0.01 |
| Robust5 | 0.7<br>0.75<br>0.8 | 75.35<br>80.62<br>− | 0.00<br>0.00<br>0.01 | 0.00<br>0.00<br>0.00 |
| Robust6 | 0.7<br>0.75<br>0.8 | 59.98<br>224.33<br>− | 0.02<br>0.05<br>0.09 | 0.00<br>0.00<br>0.00 | | 1 |
| | | | Qine | |
| --- | --- | --- | --- | --- |
| problem | ratio | Rsolver | 2B | 2B+ |
| Circle | 0.98<br>0.99<br>0.999 | 55.67<br>169.51<br>− | 0.90<br>2.32<br>69.18 | 1.03<br>2.22<br>31.55 |
| PathPoint | 0.6<br>0.65<br>0.7 | 122.72<br>334.34<br>− | 0.01<br>0.01<br>0.02 | 0.01<br>0.02<br>0.03 |
| Parabola | 0.96<br>0.97<br>0.98 | 48.33<br>130.30<br>− | 1.47<br>2.74<br>8.77 | 1.36<br>1.92<br>6.59 |
| Robot | 0.98<br>0.99<br>0.999 | 10.34<br>26.74<br>− | 0.06<br>0.14<br>5.37 | 0.08<br>0.18<br>4.08 | | | 110 | 1.7M | 6.61 |
| --- | --- | --- |
| 28 | 36.5M | 4.17 |
| 1001 | 10.2M | 4.62 |
| 40<br>100<br>100<br>190 | 1.0M<br>7.0M<br>27.2M<br>25.6M | 5.24<br>4.10<br>3.74<br>3.46 |
| -<br>- | -<br>11.2M | 7.32<br>6.92 |
| 15<br>20<br>39<br>39 | 4.2M<br>2.5M<br>7.1M<br>37.4M | 5.50<br>6.01<br>4.47<br>3.65 |
| 25<br>37<br>19<br>22 | -<br>-<br>6.1M<br>39.8M | 3.60<br>3.80<br>4.38<br>3.54 | | 0 |
| FilterShape |
| --- |
| 3×3×51 |
| 3×3×46 |
| 3×3×55 |
| 3×3×85 |
| 3×3×16 |
| 3×3×84 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 | | | 3×3×126 |
| --- |
| 3×3×16 |
| 3×3×84 | | 1 |
| FilterShape |
| --- |
| 3×3×51 |
| 3×3×46 |
| 3×3×55 |
| 3×3×85 |
| 3×3×16 |
| 3×3×84 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 | | | FilterShape |
| --- |
| 1×1×1 |
| 5×5×29 |
| 3×3×59 |
| 3×3×74 |
| 1×300 |
| 1×300 |
| Classifier | | 0 |
| FilterShape |
| --- |
| 3×3×51 |
| 3×3×46 |
| 3×3×55 |
| 3×3×85 |
| 3×3×16 | | | 3×3×84 |
| --- |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×24 |
| 3×3×126 |
| 3×3×16 |
| 3×3×84 | | 1 |
| FilterShape |
| --- |
| 3×3×51 |
| 3×3×46 |
| 3×3×55 |
| 3×3×85 |
| 3×3×16 | | | 3×3×74 |
| --- |
| 1×300 |
| 1×300 |
| Classifier | | 0 |
| T(IoU) | Atelectasis | Cardiomegaly | Effusion | Infiltration | Mass | Nodule |
| --- | --- | --- | --- | --- | --- | --- |
| Acc. | 0.6888 | 0.9383 | 0.6601 | 0.7073 | 0.4000 | 0.1392 |
| AFP | 0.8943 | 0.5996 | 0.8343 | 0.6250 | 0.6666 | 0.6077 |
| Acc. | 0.4722 | 0.6849 | 0.4509 | 0.4796 | 0.2588 | 0.0506 |
| AFP | 0.9827 | 0.7205 | 0.9096 | 0.6849 | 0.6941 | 0.6158 |
| Acc. | 0.2444 | 0.4589 | 0.3006 | 0.2764 | 0.1529 | 0.0379 |
| AFP | 1.0417 | 0.7815 | 0.9472 | 0.7236 | 0.7073 | 0.6168 | | | Acc. | 0.0944 | 0.2808 | 0.2026 | 0.1219 | 0.0705 | 0.0126 |
| --- | --- | --- | --- | --- | --- | --- |
| AFP | 1.0783 | 0.8140 | 0.9705 | 0.7489 | 0.7164 | 0.6189 |
| Acc. | 0.0500 | 0.1780 | 0.1111 | 0.0650 | 0.0117 | 0.0126 |
| AFP | 1.0884 | 0.8354 | 0.9919 | 0.7571 | 0.7215 | 0.6189 |
| Acc. | 0.0222 | 0.0753 | 0.0457 | 0.0243 | 0.0000 | 0.0126 |
| AFP | 1.0935 | 0.8506 | 1.0051 | 0.7632 | 0.7226 | 0.6189 |
| Acc. | 0.0055 | 0.0273 | 0.0196 | 0.0000 | 0.0000 | 0.0000 |
| AFP | 1.0965 | 0.8577 | 1.009 | 0.7663 | 0.7226 | 0.6199 | | 1 |
| T(IoU) | Atelectasis | Cardiomegaly | Effusion | Infiltration | Mass | Nodule |
| --- | --- | --- | --- | --- | --- | --- |
| Acc. | 0.6888 | 0.9383 | 0.6601 | 0.7073 | 0.4000 | 0.1392 |
| AFP | 0.8943 | 0.5996 | 0.8343 | 0.6250 | 0.6666 | 0.6077 |
| Acc. | 0.4722 | 0.6849 | 0.4509 | 0.4796 | 0.2588 | 0.0506 |
| AFP | 0.9827 | 0.7205 | 0.9096 | 0.6849 | 0.6941 | 0.6158 |
| Acc. | 0.2444 | 0.4589 | 0.3006 | 0.2764 | 0.1529 | 0.0379 |
| AFP | 1.0417 | 0.7815 | 0.9472 | 0.7236 | 0.7073 | 0.6168 | | | | Wanget.al | Yaoet.al | Rajpurkaret.al | BR* | PWE* | C-BR* |
| --- | --- | --- | --- | --- | --- | --- |
| Atelectasis | 0.7158 | 0.772 | 0.8209 | 0.7453 | 0.7158 | 0.7618 |
| Cardiomegaly | 0.8065 | 0.904 | 0.9048 | 0.8947 | 0.8777 | 0.9133 |
| Effusion | 0.7843 | 0.859 | 0.8831 | 0.8396 | 0.8507 | 0.8635 |
| Infiltration | 0.6089 | 0.695 | 0.7204 | 0.67 | 0.666 | 0.6923 |
| Mass | 0.7057 | 0.792 | 0.8618 | 0.6964 | 0.7137 | 0.7502 |
| Nodule | 0.6706 | 0.717 | 0.7766 | 0.6134 | 0.6023 | 0.6662 |
| Pneumonia | 0.6326 | 0.713 | 0.7632 | 0.55108 | 0.6073 | 0.7145 |
| Pneumothorax | 0.8055 | 0.841 | 0.8932 | 0.8198 | 0.8408 | 0.8594 |
| Consolidation | 0.7078 | 0.788 | 0.7939 | 0.7606 | 0.7324 | 0.7838 |
| Edema | 0.8345 | 0.882 | 0.8932 | 0.8669 | 0.8563 | 0.8880 |
| Emphysema | 0.8149 | 0.829 | 0.926 | 0.8474 | 0.8993 | 0.8982 |
| Fibrosis | 0.7688 | 0.767 | 0.8044 | 0.7236 | 0.7171 | 0.7559 |
| PT | 0.7082 | 0.765 | 0.8138 | 0.7405 | 0.7388 | 0.7739 |
| Hernia | 0.7667 | 0.914 | 0.9387 | 0.7122 | 0.898 | 0.8024 | | 0 |
| T(IoU) | Atelectasis | Cardiomegaly | Effusion | Infiltration | Mass | Nodule |
| --- | --- | --- | --- | --- | --- | --- |
| Acc. | 0.6888 | 0.9383 | 0.6601 | 0.7073 | 0.4000 | 0.1392 |
| AFP | 0.8943 | 0.5996 | 0.8343 | 0.6250 | 0.6666 | 0.6077 |
| Acc. | 0.4722 | 0.6849 | 0.4509 | 0.4796 | 0.2588 | 0.0506 |
| AFP | 0.9827 | 0.7205 | 0.9096 | 0.6849 | 0.6941 | 0.6158 |
| Acc. | 0.2444 | 0.4589 | 0.3006 | 0.2764 | 0.1529 | 0.0379 |
| AFP | 1.0417 | 0.7815 | 0.9472 | 0.7236 | 0.7073 | 0.6168 |
| Acc. | 0.0944 | 0.2808 | 0.2026 | 0.1219 | 0.0705 | 0.0126 | | | AFP | 1.0783 | 0.8140 | 0.9705 | 0.7489 | 0.7164 | 0.6189 |
| --- | --- | --- | --- | --- | --- | --- |
| Acc. | 0.0500 | 0.1780 | 0.1111 | 0.0650 | 0.0117 | 0.0126 |
| AFP | 1.0884 | 0.8354 | 0.9919 | 0.7571 | 0.7215 | 0.6189 |
| Acc. | 0.0222 | 0.0753 | 0.0457 | 0.0243 | 0.0000 | 0.0126 |
| AFP | 1.0935 | 0.8506 | 1.0051 | 0.7632 | 0.7226 | 0.6189 |
| Acc. | 0.0055 | 0.0273 | 0.0196 | 0.0000 | 0.0000 | 0.0000 |
| AFP | 1.0965 | 0.8577 | 1.009 | 0.7663 | 0.7226 | 0.6199 | | 1 |
| T(IoU) | Atelectasis | Cardiomegaly | Effusion | Infiltration | Mass | Nodule |
| --- | --- | --- | --- | --- | --- | --- |
| Acc. | 0.6888 | 0.9383 | 0.6601 | 0.7073 | 0.4000 | 0.1392 |
| AFP | 0.8943 | 0.5996 | 0.8343 | 0.6250 | 0.6666 | 0.6077 |
| Acc. | 0.4722 | 0.6849 | 0.4509 | 0.4796 | 0.2588 | 0.0506 |
| AFP | 0.9827 | 0.7205 | 0.9096 | 0.6849 | 0.6941 | 0.6158 |
| Acc. | 0.2444 | 0.4589 | 0.3006 | 0.2764 | 0.1529 | 0.0379 |
| AFP | 1.0417 | 0.7815 | 0.9472 | 0.7236 | 0.7073 | 0.6168 |
| Acc. | 0.0944 | 0.2808 | 0.2026 | 0.1219 | 0.0705 | 0.0126 | | | Pneumothorax | 0.8055 | 0.841 | 0.8932 | 0.8198 | 0.8408 | 0.8594 |
| --- | --- | --- | --- | --- | --- | --- |
| Consolidation | 0.7078 | 0.788 | 0.7939 | 0.7606 | 0.7324 | 0.7838 |
| Edema | 0.8345 | 0.882 | 0.8932 | 0.8669 | 0.8563 | 0.8880 |
| Emphysema | 0.8149 | 0.829 | 0.926 | 0.8474 | 0.8993 | 0.8982 |
| Fibrosis | 0.7688 | 0.767 | 0.8044 | 0.7236 | 0.7171 | 0.7559 |
| PT | 0.7082 | 0.765 | 0.8138 | 0.7405 | 0.7388 | 0.7739 |
| Hernia | 0.7667 | 0.914 | 0.9387 | 0.7122 | 0.898 | 0.8024 | | 0 |
| 1 | 100 | 0.5 | 46.889 |
| --- | --- | --- | --- |
| 1 | 100 | 0.5 | 110.956 |
| 1 | 100 | 0.5 | 135.143 |
| 2 | 100 | 0.5 | 46.844 |
| 3 | 100 | 0.5 | 47.029 |
| 1 | 200 | 0.5 | 49.069 |
| 1 | 300 | 0.5 | 50.632 |
| 1 | 400 | 0.5 | 54.916 | | | 1 | 100 | 0 | 45.034 |
| --- | --- | --- | --- |
| 1 | 100 | 0.1 | 47.353 | | 1 |
| 1 | 100 | 0.5 | 46.889 |
| --- | --- | --- | --- |
| 1 | 100 | 0.5 | 110.956 |
| 1 | 100 | 0.5 | 135.143 |
| 2 | 100 | 0.5 | 46.844 |
| 3 | 100 | 0.5 | 47.029 |
| 1 | 200 | 0.5 | 49.069 |
| 1 | 300 | 0.5 | 50.632 |
| 1 | 400 | 0.5 | 54.916 | | | 1 | 100 | 0.5 | 35.137 |
| --- | --- | --- | --- |
| 1 | 100 | 0.5 | 82.415 |
| 1 | 100 | 0.5 | 100.414 |
| 2 | 100 | 0.5 | 35.301 |
| 3 | 100 | 0.5 | 35.564 |
| 1 | 200 | 0.5 | 36.480 |
| 1 | 300 | 0.5 | 37.645 |
| 1 | 400 | 0.5 | 41.113 |
| 1 | 100 | 0 | 33.621 |
| 1 | 100 | 0.1 | 34.934 | | 0 |
| 1 | 100 | 0.5 | 46.889 |
| --- | --- | --- | --- |
| 1 | 100 | 0.5 | 110.956 |
| 1 | 100 | 0.5 | 135.143 |
| 2 | 100 | 0.5 | 46.844 |
| 3 | 100 | 0.5 | 47.029 |
| 1 | 200 | 0.5 | 49.069 | | | 1 | 300 | 0.5 | 50.632 |
| --- | --- | --- | --- |
| 1 | 400 | 0.5 | 54.916 |
| 1 | 100 | 0 | 45.034 |
| 1 | 100 | 0.1 | 47.353 | | 1 |
| 1 | 100 | 0.5 | 46.889 |
| --- | --- | --- | --- |
| 1 | 100 | 0.5 | 110.956 |
| 1 | 100 | 0.5 | 135.143 |
| 2 | 100 | 0.5 | 46.844 |
| 3 | 100 | 0.5 | 47.029 |
| 1 | 200 | 0.5 | 49.069 | | | 1 | 100 | 0 | 33.621 |
| --- | --- | --- | --- |
| 1 | 100 | 0.1 | 34.934 | | 0 |
| Database | Onenode | 4nodeswith<br>com.time | 4nodes<br>withoutcom.<br>time | com.time | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Win | Linux | Win | Linux | Win | Linux | Win | Linux | | | Drosoph | 0.08 | 0.06 | 0.038 | 0.023 | 0.0235 | 0.0188 | 0.0145 | 0.0042 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Pataa | 0.5 | 0.4 | 0.1344 | 0.1 | 0.0184 | 0.014 | 0.116 | 0.086 |
| estothers | 1 | 0.8 | 0.5799 | 0.421 | 0.0343 | 0.035 | 0.5456 | 0.386 |
| envnr | 18 | 15 | 4.0308 | 3.5132 | 0.5308 | 0.5132 | 3.5 | 3 |
| Nr | 27 | 24 | 7.2077 | 6.1163 | 0.4077 | 0.6163 | 6.8 | 5.5 | | 1 |
| Database | Onenode | 4nodeswith<br>com.time | 4nodes<br>withoutcom.<br>time | com.time | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Win | Linux | Win | Linux | Win | Linux | Win | Linux | | | nqubits | ngates | Total<br>Time(s) | Timeper<br>Gate(s) |
| --- | --- | --- | --- |
| 29 | 435 | 116.6 | 0.27 |
| 30 | 465 | 141.6 | 0.30 |
| 31 | 496 | 167.9 | 0.34 |
| 32 | 528 | 200.9 | 0.38 |
| 33 | 561 | 245.0 | 0.44 |
| 34 | 595 | 297.4 | 0.50 |
| 35 | 630 | 339.7 | 0.54 |
| 36 | 666 | 445.4 | 0.67 |
| 37 | 703 | 540.2 | 0.77 |
| 38 | 741 | 643.8 | 0.87 |
| 39 | 780 | 766.1 | 0.98 |
| 40 | 820 | 997.2 | 1.22 | | 0 |
| Database | Onenode | 4nodeswith<br>com.time | 4nodes<br>withoutcom.<br>time | com.time | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Win | Linux | Win | Linux | Win | Linux | Win | Linux |
| Drosoph | 0.08 | 0.06 | 0.038 | 0.023 | 0.0235 | 0.0188 | 0.0145 | 0.0042 |
| Pataa | 0.5 | 0.4 | 0.1344 | 0.1 | 0.0184 | 0.014 | 0.116 | 0.086 |
| estothers | 1 | 0.8 | 0.5799 | 0.421 | 0.0343 | 0.035 | 0.5456 | 0.386 | | | envnr | 18 | 15 | 4.0308 | 3.5132 | 0.5308 | 0.5132 | 3.5 | 3 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Nr | 27 | 24 | 7.2077 | 6.1163 | 0.4077 | 0.6163 | 6.8 | 5.5 | | 1 |
| Database | Onenode | 4nodeswith<br>com.time | 4nodes<br>withoutcom.<br>time | com.time | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Win | Linux | Win | Linux | Win | Linux | Win | Linux |
| Drosoph | 0.08 | 0.06 | 0.038 | 0.023 | 0.0235 | 0.0188 | 0.0145 | 0.0042 |
| Pataa | 0.5 | 0.4 | 0.1344 | 0.1 | 0.0184 | 0.014 | 0.116 | 0.086 |
| estothers | 1 | 0.8 | 0.5799 | 0.421 | 0.0343 | 0.035 | 0.5456 | 0.386 | | | 38 | 741 | 643.8 | 0.87 |
| --- | --- | --- | --- |
| 39 | 780 | 766.1 | 0.98 |
| 40 | 820 | 997.2 | 1.22 | | 0 |
| | | | |
| --- | --- | --- | --- |
| | Factor1:EaseofUse | Factor2:CognitiveEfforts | Factor3:Trust |
| Convenient | 0.91 | 0.05 | -0.02 |
| Quick | 0.84 | -0.12 | -0.15 |
| Enjoy | 0.77 | 0.15 | 0.12 |
| Reuse | 0.75 | 0.04 | 0.19 |
| Helpful | 0.72 | 0.02 | 0.17 |
| NoEnjoy | -0.52 | 0.22 | -0.16 |
| UserFriendly | 0.42 | -0.19 | 0.37 |
| NeedInstructions | 0.15 | 0.80 | -0.12 |
| Concentrate | 0.03 | 0.64 | 0.14 |
| Stressful | -0.41 | 0.51 | 0.01 |
| Match | -0.30 | 0.42 | -0.15 |
| Frustrating | -0.47 | 0.47 | 0.00 | | | Trust | 0.08 | -0.04 | 0.80 |
| --- | --- | --- | --- |
| Secure | -0.02 | 0.03 | 0.82 |
| Easy | 0.27 | -0.28 | 0.31 |
| Eigenvalues | 7.52 | 1.78 | 1.03 | | 1 |
| | | | |
| --- | --- | --- | --- |
| | Factor1:EaseofUse | Factor2:CognitiveEfforts | Factor3:Trust |
| Convenient | 0.91 | 0.05 | -0.02 |
| Quick | 0.84 | -0.12 | -0.15 |
| Enjoy | 0.77 | 0.15 | 0.12 |
| Reuse | 0.75 | 0.04 | 0.19 |
| Helpful | 0.72 | 0.02 | 0.17 |
| NoEnjoy | -0.52 | 0.22 | -0.16 |
| UserFriendly | 0.42 | -0.19 | 0.37 |
| NeedInstructions | 0.15 | 0.80 | -0.12 |
| Concentrate | 0.03 | 0.64 | 0.14 |
| Stressful | -0.41 | 0.51 | 0.01 |
| Match | -0.30 | 0.42 | -0.15 |
| Frustrating | -0.47 | 0.47 | 0.00 | | | SearchScore | ScoreChange | DiscountFactor | ContributiontoTotalError |
| --- | --- | --- | --- |
| 10 | 0 | 0.7 | 0 |
| 20 | 10 | 0.7 | 7 |
| 20 | 0 | 0.7 | 0 |
| 20 | 0 | 0.7 | 0 |
| -10 | -30 | 0.7 | -7.2 |
| -10 | 0 | 0.7 | 0 |
| -10 | 0 | 0.7 | 0 |
| 40 | 50 | 0.7 | 4.12 |
| 40 | 0 | 0.7 | 0 |
| 40 | 0 | 0.7 | 0 |
| 40 | 0 | 0.7 | 0 |
| 40 | 0 | 0.7 | 0 | | 0 |
| | | | |
| --- | --- | --- | --- |
| | Factor1:EaseofUse | Factor2:CognitiveEfforts | Factor3:Trust |
| Convenient | 0.91 | 0.05 | -0.02 |
| Quick | 0.84 | -0.12 | -0.15 | | | Enjoy | 0.77 | 0.15 | 0.12 |
| --- | --- | --- | --- |
| Reuse | 0.75 | 0.04 | 0.19 |
| Helpful | 0.72 | 0.02 | 0.17 |
| NoEnjoy | -0.52 | 0.22 | -0.16 |
| UserFriendly | 0.42 | -0.19 | 0.37 |
| NeedInstructions | 0.15 | 0.80 | -0.12 |
| Concentrate | 0.03 | 0.64 | 0.14 |
| Stressful | -0.41 | 0.51 | 0.01 |
| Match | -0.30 | 0.42 | -0.15 |
| Frustrating | -0.47 | 0.47 | 0.00 |
| Trust | 0.08 | -0.04 | 0.80 |
| Secure | -0.02 | 0.03 | 0.82 |
| Easy | 0.27 | -0.28 | 0.31 |
| Eigenvalues | 7.52 | 1.78 | 1.03 | | 1 |
| | | | |
| --- | --- | --- | --- |
| | Factor1:EaseofUse | Factor2:CognitiveEfforts | Factor3:Trust |
| Convenient | 0.91 | 0.05 | -0.02 |
| Quick | 0.84 | -0.12 | -0.15 | | | 40 | 50 | 0.7 | 4.12 |
| --- | --- | --- | --- |
| 40 | 0 | 0.7 | 0 |
| 40 | 0 | 0.7 | 0 |
| 40 | 0 | 0.7 | 0 |
| 40 | 0 | 0.7 | 0 | | 0 |
| Euro2016TrainModel-J48 | | | |
| --- | --- | --- | --- |
| Time | Precision | Recall | F-Measure |
| 1 | 0.990 | 0.986 | 0.986 |
| 2 | 0.978 | 0.977 | 0.977 |
| 3 | 0.990 | 0.990 | 0.990 | | | 4 | 0.994 | 0.994 | 0.994 |
| --- | --- | --- | --- |
| 5 | 0.996 | 0.996 | 0.996 |
| 6 | 0.995 | 0.995 | 0.995 |
| 7 | 0.996 | 0.996 | 0.996 |
| 8 | 0.997 | 0.997 | 0.997 |
| 9 | 0.997 | 0.997 | 0.997 |
| 10 | 0.998 | 0.998 | 0.998 | | 1 |
| Euro2016TrainModel-J48 | | | |
| --- | --- | --- | --- |
| Time | Precision | Recall | F-Measure |
| 1 | 0.990 | 0.986 | 0.986 |
| 2 | 0.978 | 0.977 | 0.977 |
| 3 | 0.990 | 0.990 | 0.990 | | | Euro2016TrainModel-MLP | | | |
| --- | --- | --- | --- |
| Time | Precision | Recall | F-Measure |
| 1 | 0.988 | 0.975 | 0.978 |
| 2 | 0.987 | 0.987 | 0.987 |
| 3 | 0.993 | 0.993 | 0.993 |
| 4 | 0.994 | 0.994 | 0.994 |
| 5 | 0.994 | 0.994 | 0.994 |
| 6 | 0.995 | 0.995 | 0.995 |
| 7 | 0.9975 | 0.9975 | 0.9975 |
| 8 | 0.996 | 0.996 | 0.996 |
| 9 | 0.995 | 0.995 | 0.995 |
| 10 | 0.9978 | 0.9978 | 0.9978 | | 0 |
| Euro2016TrainModel-J48 | | | |
| --- | --- | --- | --- |
| Time | Precision | Recall | F-Measure |
| 1 | 0.990 | 0.986 | 0.986 |
| 2 | 0.978 | 0.977 | 0.977 |
| 3 | 0.990 | 0.990 | 0.990 | | | 4 | 0.994 | 0.994 | 0.994 |
| --- | --- | --- | --- |
| 5 | 0.996 | 0.996 | 0.996 |
| 6 | 0.995 | 0.995 | 0.995 |
| 7 | 0.996 | 0.996 | 0.996 |
| 8 | 0.997 | 0.997 | 0.997 |
| 9 | 0.997 | 0.997 | 0.997 |
| 10 | 0.998 | 0.998 | 0.998 | | 1 |
| Euro2016TrainModel-J48 | | | |
| --- | --- | --- | --- |
| Time | Precision | Recall | F-Measure |
| 1 | 0.990 | 0.986 | 0.986 |
| 2 | 0.978 | 0.977 | 0.977 |
| 3 | 0.990 | 0.990 | 0.990 | | | 4 | 0.994 | 0.994 | 0.994 |
| --- | --- | --- | --- |
| 5 | 0.994 | 0.994 | 0.994 |
| 6 | 0.995 | 0.995 | 0.995 |
| 7 | 0.9975 | 0.9975 | 0.9975 |
| 8 | 0.996 | 0.996 | 0.996 |
| 9 | 0.995 | 0.995 | 0.995 |
| 10 | 0.9978 | 0.9978 | 0.9978 | | 0 |
| PRID | iLIDS-VID | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| fusemethod | r1 | r5 | r10 | r20 | r1 | r5 | r10 | r20 | mAP | r1 |
| image<br>max-pool<br>avg-pool | 29.21<br>24.72<br>47.19 | 58.43<br>47.19<br>70.79 | 75.28<br>68.54<br>77.53 | 84.27<br>86.52<br>86.52 | 8.00<br>4.00<br>12.67 | 22.00<br>12.00<br>22.67 | 30.00<br>19.33<br>29.33 | 39.33<br>24.00<br>40.67 | 6.07<br>6.26<br>9.54 | 17.68<br>17.83<br>23.74 | | | image<br>max-pool<br>avg-pool<br>TPP | 62.92<br>75.28<br>77.53<br>78.65 | 88.67<br>97.75<br>97.75<br>98.88 | 96.63<br>98.88<br>100<br>100 | 98.88<br>100<br>100<br>100 | 26.67<br>52.00<br>53.33<br>54.67 | 52.67<br>76.67<br>77.33<br>78.67 | 63.33<br>86.67<br>88.67<br>88.67 | 74.67<br>92.00<br>93.33<br>93.33 | 35.00<br>44.74<br>51.47<br>51.95 | 52.58<br>65.91<br>67.08<br>68.54 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| image<br>max-pool<br>avg-pool | 64.04<br>79.77<br>80.90 | 88.67<br>98.88<br>100 | 97.75<br>100<br>100 | 98.88<br>100<br>100 | 28.00<br>54.67<br>55.33 | 60.00<br>78.00<br>78.67 | 72.00<br>89.33<br>88.67 | 84.67<br>95.33<br>96.67 | 35.64<br>50.06<br>52.00 | 53.43<br>68.69<br>68.79 |
| TPP | 82.02 | 100 | 100 | 100 | 56.67 | 78.67 | 90.00 | 96.67 | 52.55 | 69.69 | | 1 |
| PRID | iLIDS-VID | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| fusemethod | r1 | r5 | r10 | r20 | r1 | r5 | r10 | r20 | mAP | r1 |
| image<br>max-pool<br>avg-pool | 29.21<br>24.72<br>47.19 | 58.43<br>47.19<br>70.79 | 75.28<br>68.54<br>77.53 | 84.27<br>86.52<br>86.52 | 8.00<br>4.00<br>12.67 | 22.00<br>12.00<br>22.67 | 30.00<br>19.33<br>29.33 | 39.33<br>24.00<br>40.67 | 6.07<br>6.26<br>9.54 | 17.68<br>17.83<br>23.74 | | | H1 | H2open | SNE | SAD | SMD | SDV | SCC | SPL | SAPD | SED | SCL |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 199 | 125302 | 1049866 | 6.62 | 343 | 100.15 | 0.306 | 2.245 | 7.69 | 9 | 7.46 |
| 72.9<br>41.1<br>19.7 | 40712.1<br>24618.2<br>7771.4 | 1048153<br>1035994<br>991498 | 6.61<br>6.53<br>6.25 | 316.0<br>186.0<br>164.9 | 97.46<br>86.47<br>64.20 | 0.303<br>0.294<br>0.284 | 2.244<br>2.248<br>2.265 | 7.74<br>7.82<br>8.08 | 9.4<br>9.5<br>10.0 | 7.50<br>7.59<br>7.85 |
| 153 | 113338 | 925872 | 5.53 | 549 | 33.20 | 0.205 | 2.336 | 12.75 | 16 | 12.10 |
| 55.7<br>34.5<br>19.2 | 55655.9<br>39689.8<br>16375.4 | 924321<br>915711<br>892140 | 5.52<br>5.47<br>5.33 | 479.1<br>299.7<br>253.9 | 31.73<br>27.18<br>21.87 | 0.206<br>0.220<br>0.232 | 2.340<br>2.348<br>2.374 | 12.14<br>12.40<br>12.52 | 15.2<br>15.6<br>15.5 | 11.65<br>11.91<br>12.06 |
| 978 | 321724 | 2987624 | 5.27 | 28754 | 2576.0 | 0.0062 | 2.429 | 6.07 | 8 | 6.79 |
| 157.2<br>80.0<br>23.4 | 36744.6<br>22361.7<br>5806.9 | 2982974<br>2940310<br>2624066 | 5.26<br>5.18<br>4.62 | 28438<br>26900<br>16353 | 2522.6<br>2282.6<br>970.8 | 0.0062<br>0.0061<br>0.0070 | 2.416<br>2.419<br>2.438 | 6.24<br>6.27<br>6.59 | 8.0<br>8.0<br>8.1 | 6.01<br>6.04<br>6.36 | | 0 |
| PRID | iLIDS-VID | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| fusemethod | r1 | r5 | r10 | r20 | r1 | r5 | r10 | r20 | mAP | r1 | | | image<br>max-pool<br>avg-pool | 29.21<br>24.72<br>47.19 | 58.43<br>47.19<br>70.79 | 75.28<br>68.54<br>77.53 | 84.27<br>86.52<br>86.52 | 8.00<br>4.00<br>12.67 | 22.00<br>12.00<br>22.67 | 30.00<br>19.33<br>29.33 | 39.33<br>24.00<br>40.67 | 6.07<br>6.26<br>9.54 | 17.68<br>17.83<br>23.74 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| image<br>max-pool<br>avg-pool<br>TPP | 62.92<br>75.28<br>77.53<br>78.65 | 88.67<br>97.75<br>97.75<br>98.88 | 96.63<br>98.88<br>100<br>100 | 98.88<br>100<br>100<br>100 | 26.67<br>52.00<br>53.33<br>54.67 | 52.67<br>76.67<br>77.33<br>78.67 | 63.33<br>86.67<br>88.67<br>88.67 | 74.67<br>92.00<br>93.33<br>93.33 | 35.00<br>44.74<br>51.47<br>51.95 | 52.58<br>65.91<br>67.08<br>68.54 |
| image<br>max-pool<br>avg-pool | 64.04<br>79.77<br>80.90 | 88.67<br>98.88<br>100 | 97.75<br>100<br>100 | 98.88<br>100<br>100 | 28.00<br>54.67<br>55.33 | 60.00<br>78.00<br>78.67 | 72.00<br>89.33<br>88.67 | 84.67<br>95.33<br>96.67 | 35.64<br>50.06<br>52.00 | 53.43<br>68.69<br>68.79 |
| TPP | 82.02 | 100 | 100 | 100 | 56.67 | 78.67 | 90.00 | 96.67 | 52.55 | 69.69 | | 1 |
| PRID | iLIDS-VID | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| fusemethod | r1 | r5 | r10 | r20 | r1 | r5 | r10 | r20 | mAP | r1 | | | 978 | 321724 | 2987624 | 5.27 | 28754 | 2576.0 | 0.0062 | 2.429 | 6.07 | 8 | 6.79 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 157.2<br>80.0<br>23.4 | 36744.6<br>22361.7<br>5806.9 | 2982974<br>2940310<br>2624066 | 5.26<br>5.18<br>4.62 | 28438<br>26900<br>16353 | 2522.6<br>2282.6<br>970.8 | 0.0062<br>0.0061<br>0.0070 | 2.416<br>2.419<br>2.438 | 6.24<br>6.27<br>6.59 | 8.0<br>8.0<br>8.1 | 6.01<br>6.04<br>6.36 | | 0 |
| Memory(MB) | Priceper100ms($) |
| --- | --- |
| 128 | 0.000000208 |
| 256 | 0.000000417 |
| 384 | 0.000000625 |
| 512 | 0.000000834 |
| 640 | 0.000001042 |
| 768 | 0.00000125 |
| 896 | 0.000001459 |
| 1024 | 0.000001667 | | | 1152 | 0.000001875 |
| --- | --- |
| 1280 | 0.000002084 |
| 1408 | 0.000002292 |
| 1536 | 0.000002501 | | 1 |
| Memory(MB) | Priceper100ms($) |
| --- | --- |
| 128 | 0.000000208 |
| 256 | 0.000000417 |
| 384 | 0.000000625 |
| 512 | 0.000000834 |
| 640 | 0.000001042 |
| 768 | 0.00000125 |
| 896 | 0.000001459 |
| 1024 | 0.000001667 | | | | | | | | |
| --- | --- | --- | --- | --- | --- |
| | | | | | |
| 2 | 0.315 | 97Mb | 2 | 0.345 | 256Mb |
| 2 | 0.282 | 388Mb | 2 | 0.321 | 1024Mb |
| 2 | 0.259 | 1552Mb | 2 | 0.305 | 4096Mb | | 0 |
| Memory(MB) | Priceper100ms($) |
| --- | --- |
| 128 | 0.000000208 |
| 256 | 0.000000417 |
| 384 | 0.000000625 |
| 512 | 0.000000834 |
| 640 | 0.000001042 |
| 768 | 0.00000125 | | | 896 | 0.000001459 |
| --- | --- |
| 1024 | 0.000001667 |
| 1152 | 0.000001875 |
| 1280 | 0.000002084 |
| 1408 | 0.000002292 |
| 1536 | 0.000002501 | | 1 |
| Memory(MB) | Priceper100ms($) |
| --- | --- |
| 128 | 0.000000208 |
| 256 | 0.000000417 |
| 384 | 0.000000625 |
| 512 | 0.000000834 |
| 640 | 0.000001042 |
| 768 | 0.00000125 | | | 2 | 0.315 | 97Mb | 2 | 0.345 | 256Mb |
| --- | --- | --- | --- | --- | --- |
| 2 | 0.282 | 388Mb | 2 | 0.321 | 1024Mb |
| 2 | 0.259 | 1552Mb | 2 | 0.305 | 4096Mb | | 0 |
| Model | SST-1 | SST-2 | IMDB | Books | DVDs | Electronics | Kitchen | QC |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| NBOW | 42.4 | 80.5 | 83.62 | - | - | - | - | 88.2 |
| PV | 44.6 | 82.7 | 91.7 | - | - | - | - | 91.8 |
| MT-RNN | 49.6 | 87.9 | 91.3 | - | - | - | - | - | | | MT-CNN | - | - | - | 80.2 | 81.0 | 83.4 | 83.0 | - |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MT-DNN | - | - | - | 79.7 | 80.5 | 82.5 | 82.8 | - |
| GRNN | 47.5 | 85.5 | - | - | - | - | - | 93.8 |
| OurModel | 49.2 | 87.7 | 91.6 | 83.5 | 84.0 | 86.2 | 84.8 | 92.3 | | 1 |
| Model | SST-1 | SST-2 | IMDB | Books | DVDs | Electronics | Kitchen | QC |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| NBOW | 42.4 | 80.5 | 83.62 | - | - | - | - | 88.2 |
| PV | 44.6 | 82.7 | 91.7 | - | - | - | - | 91.8 |
| MT-RNN | 49.6 | 87.9 | 91.3 | - | - | - | - | - | | | Model | WERSWB | WERCH | | |
| --- | --- | --- | --- | --- |
| CE | ST | CE | ST | |
| CNN | 12.6 | 10.4 | 18.4 | 17.9 |
| DNN | 11.7 | 10.3 | 18.5 | 17.0 |
| RNN | 11.5 | 9.9 | 17.7 | 16.3 |
| DNN+CNN | 11.3 | 9.6 | 17.4 | 16.3 |
| RNN+CNN | 11.2 | 9.4 | 17.0 | 16.1 |
| DNN+RNN+CNN | 11.1 | 9.4 | 17.1 | 15.9 | | 0 |
| Model | SST-1 | SST-2 | IMDB | Books | DVDs | Electronics | Kitchen | QC |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| NBOW | 42.4 | 80.5 | 83.62 | - | - | - | - | 88.2 |
| PV | 44.6 | 82.7 | 91.7 | - | - | - | - | 91.8 | | | MT-RNN | 49.6 | 87.9 | 91.3 | - | - | - | - | - |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MT-CNN | - | - | - | 80.2 | 81.0 | 83.4 | 83.0 | - |
| MT-DNN | - | - | - | 79.7 | 80.5 | 82.5 | 82.8 | - |
| GRNN | 47.5 | 85.5 | - | - | - | - | - | 93.8 |
| OurModel | 49.2 | 87.7 | 91.6 | 83.5 | 84.0 | 86.2 | 84.8 | 92.3 | | 1 |
| Model | SST-1 | SST-2 | IMDB | Books | DVDs | Electronics | Kitchen | QC |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| NBOW | 42.4 | 80.5 | 83.62 | - | - | - | - | 88.2 |
| PV | 44.6 | 82.7 | 91.7 | - | - | - | - | 91.8 | | | DNN+CNN | 11.3 | 9.6 | 17.4 | 16.3 |
| --- | --- | --- | --- | --- |
| RNN+CNN | 11.2 | 9.4 | 17.0 | 16.1 |
| DNN+RNN+CNN | 11.1 | 9.4 | 17.1 | 15.9 | | 0 |
| Dataset | #Updates | LT | IC | | |
| --- | --- | --- | --- | --- | --- |
| Total | ST | Total | ST | | |
| wiki-Vote | 2.1×10 | 11.3 | 2.3 | 29.3 | 8.2 |
| Flixster | 2.2×10 | 266 | 28 | 522 | 85 |
| soc-Pokec | 6.4×10 | 3165 | 311 | 4461 | 735 | | | flickr-growth | 7.8×10 | 1908 | 201 | 3223 | 935 |
| --- | --- | --- | --- | --- | --- |
| Twitter | 3.0×10 | 15369 | 375 | 19803 | 4770 | | 1 |
| Dataset | #Updates | LT | IC | | |
| --- | --- | --- | --- | --- | --- |
| Total | ST | Total | ST | | |
| wiki-Vote | 2.1×10 | 11.3 | 2.3 | 29.3 | 8.2 |
| Flixster | 2.2×10 | 266 | 28 | 522 | 85 |
| soc-Pokec | 6.4×10 | 3165 | 311 | 4461 | 735 | | | Network | Vertices | Edges | τ | IMQueries | kmax |
| --- | --- | --- | --- | --- | --- |
| wiki-Vote | 7K | 104K | 10 | 212 | 50 |
| Flixster | 99K | 978K | 10 | 223 | 100 |
| soc-Pokec | 1.6M | 31M | 10 | 636 | 200 |
| flickr-growth | 2.3M | 33M | 10 | 779 | 200 |
| Twitter | 41.6M | 1.5G | 10 | 3011 | 500 | | 0 |
| Dataset | #Updates | LT | IC | | |
| --- | --- | --- | --- | --- | --- |
| Total | ST | Total | ST | | |
| wiki-Vote | 2.1×10 | 11.3 | 2.3 | 29.3 | 8.2 | | | Flixster | 2.2×10 | 266 | 28 | 522 | 85 |
| --- | --- | --- | --- | --- | --- |
| soc-Pokec | 6.4×10 | 3165 | 311 | 4461 | 735 |
| flickr-growth | 7.8×10 | 1908 | 201 | 3223 | 935 |
| Twitter | 3.0×10 | 15369 | 375 | 19803 | 4770 | | 1 |
| Dataset | #Updates | LT | IC | | |
| --- | --- | --- | --- | --- | --- |
| Total | ST | Total | ST | | |
| wiki-Vote | 2.1×10 | 11.3 | 2.3 | 29.3 | 8.2 | | | soc-Pokec | 1.6M | 31M | 10 | 636 | 200 |
| --- | --- | --- | --- | --- | --- |
| flickr-growth | 2.3M | 33M | 10 | 779 | 200 |
| Twitter | 41.6M | 1.5G | 10 | 3011 | 500 | | 0 |
| | VGG-F | CaffeNet | GoogLeNet | VGG-16 | VGG-19 | ResNet-152 | Mean |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Baseline | 12.62 | 12.9 | 10.29 | 8.62 | 8.40 | 8.99 | 10.30 |
| FFF(w/oData) | 81.59 | 80.92 | 56.44 | 47.10 | 43.62 | 29.78 | 56.58 | | | Ours(w/oData) | 92.37 | 89.04 | 75.28 | 71.59 | 69.45 | 60.72 | 76.41 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| UAP(wData) | 93.8 | 93.1 | 78.5 | 77.8 | 80.8 | 84.0 | 84.67 | | 1 |
| | VGG-F | CaffeNet | GoogLeNet | VGG-16 | VGG-19 | ResNet-152 | Mean |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Baseline | 12.62 | 12.9 | 10.29 | 8.62 | 8.40 | 8.99 | 10.30 |
| FFF(w/oData) | 81.59 | 80.92 | 56.44 | 47.10 | 43.62 | 29.78 | 56.58 | | | | 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 | 0.919 | 0.91 |
| 36553 | 200 | 21 | 14 | 0.905 | 0.935 | 0.92 |
| 50009 | 44 | 28 | 14 | 0.611 | 0.759 | 0.677 |
| 50028 | 81 | 17 | 12 | 0.827 | 0.871 | 0.848 |
| UGS01 | 164 | 8 | 12 | 0.953 | 0.932 | 0.943 |
| UGS04 | 218 | 25 | 5 | 0.897 | 0.978 | 0.936 |
| 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 | | 0 |
| | VGG-F | CaffeNet | GoogLeNet | VGG-16 | VGG-19 | ResNet-152 | Mean |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Baseline | 12.62 | 12.9 | 10.29 | 8.62 | 8.40 | 8.99 | 10.30 | | | FFF(w/oData) | 81.59 | 80.92 | 56.44 | 47.10 | 43.62 | 29.78 | 56.58 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Ours(w/oData) | 92.37 | 89.04 | 75.28 | 71.59 | 69.45 | 60.72 | 76.41 |
| UAP(wData) | 93.8 | 93.1 | 78.5 | 77.8 | 80.8 | 84.0 | 84.67 | | 1 |
| | VGG-F | CaffeNet | GoogLeNet | VGG-16 | VGG-19 | ResNet-152 | Mean |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Baseline | 12.62 | 12.9 | 10.29 | 8.62 | 8.40 | 8.99 | 10.30 | | | 50009 | 44 | 28 | 14 | 0.611 | 0.759 | 0.677 |
| --- | --- | --- | --- | --- | --- | --- |
| 50028 | 81 | 17 | 12 | 0.827 | 0.871 | 0.848 |
| UGS01 | 164 | 8 | 12 | 0.953 | 0.932 | 0.943 |
| UGS04 | 218 | 25 | 5 | 0.897 | 0.978 | 0.936 |
| 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 | | 0 |
| Resource | C2(E) | C2(A) | C1(E) | C1(A) |
| --- | --- | --- | --- | --- |
| ALUTs | 528 | 546 | 5764 | 5837 |
| REGs | 534 | 575 | 4504 | 4892 | | | BRAM(bits) | 5418 | 5400 | 11304 | 11250 |
| --- | --- | --- | --- | --- |
| DSPs | 0 | 0 | 0 | 0 |
| Cycles/Kernel | 292 | 308 | 180 | 185 |
| EWGT | 57K | 43K | 92K | 72K | | 1 |
| Resource | C2(E) | C2(A) | C1(E) | C1(A) |
| --- | --- | --- | --- | --- |
| ALUTs | 528 | 546 | 5764 | 5837 |
| REGs | 534 | 575 | 4504 | 4892 | | | Parameter | C2(E) | C2(A) | C1(E) | C1(A) |
| --- | --- | --- | --- | --- |
| ALUTs | 82 | 83 | 36.3K | 37.6K |
| REGs | 172 | 177 | 18.6K | 19.1K |
| BRAM(bits) | 7.20K | 7.27K | 216K | 221K |
| DSPs | 1 | 1 | 4 | 4 |
| Cycles/Kernel | 1003 | 1008 | 250 | 258 |
| EWGT | 249K | 292K | 997K | 826K | | 0 |
| Resource | C2(E) | C2(A) | C1(E) | C1(A) |
| --- | --- | --- | --- | --- |
| ALUTs | 528 | 546 | 5764 | 5837 |
| REGs | 534 | 575 | 4504 | 4892 | | | BRAM(bits) | 5418 | 5400 | 11304 | 11250 |
| --- | --- | --- | --- | --- |
| DSPs | 0 | 0 | 0 | 0 |
| Cycles/Kernel | 292 | 308 | 180 | 185 |
| EWGT | 57K | 43K | 92K | 72K | | 1 |
| Resource | C2(E) | C2(A) | C1(E) | C1(A) |
| --- | --- | --- | --- | --- |
| ALUTs | 528 | 546 | 5764 | 5837 |
| REGs | 534 | 575 | 4504 | 4892 | | | DSPs | 1 | 1 | 4 | 4 |
| --- | --- | --- | --- | --- |
| Cycles/Kernel | 1003 | 1008 | 250 | 258 |
| EWGT | 249K | 292K | 997K | 826K | | 0 |
| 2Dvs2.5Dvs3D | | | |
| --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | | Mean | Std | Mean | Std | Mean | Std |
| --- | --- | --- | --- | --- | --- | --- |
| 1 | 636.51,335.92 | 458.05,410.72 | 350.38,314.66 | 169.89,210.71 | 178.86,175.18 | 195.45,148.11 |
| 2 | 674.81,164.18 | 483.05,142.16 | 327.13,218.02 | 219.27,174.73 | 173.36,194.73 | 189.16,142.18 |
| 3 | 2227.33,590.95 | 4918.12,1079.51 | 479.55,468.34 | 412.73,281.55 | 468.56,482.34 | 297.08,207.33 |
| 4 | 986.62,824.92 | 1474.53,1737.91 | 324.51,277.44 | 178.71,210.27 | 188.61,167.71 | 192.31,133.46 |
| 5 | 945.29,208.74 | 713.39,376.67 | 875.23,304.89 | 483.12,222.61 | 699.59,195.46 | 445.35,170.75 |
| 6 | 665.61,232.86 | 468.55,366.36 | 461.98,269.71 | 276.23,187.19 | 257.11,200.81 | 209.78,137.04 |
| 7 | 660.83,239.21 | 362.87,184.25 | 519.06,236.97 | 420.72,185.22 | 604.11,173.52 | 296.58,113.85 |
| 8 | 583.52,357.65 | 312.55,245.24 | 458.31,256.74 | 425.81,224.43 | 524.19,245.41 | 308.77,170.46 |
| 9 | 625.89,360.22 | 408.87,216.06 | 463.65,375.31 | 360.06,330.94 | 377.56,304.88 | 261.53,299.25 |
| 10 | 587.73,214.97 | 410.06,487.02 | 440.14,270.42 | 295.54,218.76 | 277.06,203.33 | 252.39,171.86 |
| 11 | 728.69,468.99 | 579.65,628.01 | 490.85,837.33 | 397.51,577.42 | 447.82,571.31 | 299.31,442.53 | | 1 |
| 2Dvs2.5Dvs3D | | | |
| --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std |
| 1 | 271.91,73.74 | 120.39,54.93 | 128.29,82.42 | 61.93,57.59 | 90.72,165.98 | 52.69,88.66 |
| 2 | 272.13,74.71 | 174.92,60.23 | 104.76,74.68 | 62.57,57.42 | 78.93,110.95 | 53.01,72.12 |
| 3 | 269.11,96.05 | 643.46,198.38 | 621.51,226.25 | 357.53,103.18 | 621.03,311.18 | 344.64,91.91 |
| 4 | 448.56,317.26 | 775.57,1134.81 | 171.02,127.61 | 82.94,79.97 | 126.67,175.23 | 84.47,91.81 |
| 5 | 453.31,98.76 | 313.59,62.72 | 847.58,105.51 | 372.41,65.22 | 851.03,127.28 | 405.94,71.71 |
| 6 | 315.27,97.65 | 166.49,67.03 | 238.81,88.71 | 81.87,69.14 | 199.57,84.55 | 78.85,65.08 |
| 7 | 163.26,124.66 | 148.24,69.82 | 423.71,86.75 | 273.51,63.16 | 483.87,98.61 | 262.28,68.97 |
| 8 | 170.48,82.16 | 135.11,55.27 | 500.16,291.91 | 327.32,125.91 | 557.58,263.84 | 306.18,106.34 |
| 9 | 174.44,124.41 | 158.03,90.47 | 474.84,309.11 | 293.31,197.14 | 471.45,348.61 | 273.68,197.46 |
| 10 | 189.03,93.93 | 254.06,347.13 | 204.03,68.67 | 110.11,44.11 | 211.56,101.18 | 129.56,55.63 |
| 11 | 242.43,58.49 | 178.81,60.65 | 601.07,651.39 | 358.44,291.53 | 650.83,643.25 | 326.46,275.01 | | 0 |
| 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std |
| 1 | 636.51,335.92 | 458.05,410.72 | 350.38,314.66 | 169.89,210.71 | 178.86,175.18 | 195.45,148.11 |
| 2 | 674.81,164.18 | 483.05,142.16 | 327.13,218.02 | 219.27,174.73 | 173.36,194.73 | 189.16,142.18 |
| 3 | 2227.33,590.95 | 4918.12,1079.51 | 479.55,468.34 | 412.73,281.55 | 468.56,482.34 | 297.08,207.33 |
| 4 | 986.62,824.92 | 1474.53,1737.91 | 324.51,277.44 | 178.71,210.27 | 188.61,167.71 | 192.31,133.46 |
| 5 | 945.29,208.74 | 713.39,376.67 | 875.23,304.89 | 483.12,222.61 | 699.59,195.46 | 445.35,170.75 |
| 6 | 665.61,232.86 | 468.55,366.36 | 461.98,269.71 | 276.23,187.19 | 257.11,200.81 | 209.78,137.04 | | | 7 | 660.83,239.21 | 362.87,184.25 | 519.06,236.97 | 420.72,185.22 | 604.11,173.52 | 296.58,113.85 |
| --- | --- | --- | --- | --- | --- | --- |
| 8 | 583.52,357.65 | 312.55,245.24 | 458.31,256.74 | 425.81,224.43 | 524.19,245.41 | 308.77,170.46 |
| 9 | 625.89,360.22 | 408.87,216.06 | 463.65,375.31 | 360.06,330.94 | 377.56,304.88 | 261.53,299.25 |
| 10 | 587.73,214.97 | 410.06,487.02 | 440.14,270.42 | 295.54,218.76 | 277.06,203.33 | 252.39,171.86 |
| 11 | 728.69,468.99 | 579.65,628.01 | 490.85,837.33 | 397.51,577.42 | 447.82,571.31 | 299.31,442.53 | | 1 |
| 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std |
| 1 | 636.51,335.92 | 458.05,410.72 | 350.38,314.66 | 169.89,210.71 | 178.86,175.18 | 195.45,148.11 |
| 2 | 674.81,164.18 | 483.05,142.16 | 327.13,218.02 | 219.27,174.73 | 173.36,194.73 | 189.16,142.18 |
| 3 | 2227.33,590.95 | 4918.12,1079.51 | 479.55,468.34 | 412.73,281.55 | 468.56,482.34 | 297.08,207.33 |
| 4 | 986.62,824.92 | 1474.53,1737.91 | 324.51,277.44 | 178.71,210.27 | 188.61,167.71 | 192.31,133.46 |
| 5 | 945.29,208.74 | 713.39,376.67 | 875.23,304.89 | 483.12,222.61 | 699.59,195.46 | 445.35,170.75 |
| 6 | 665.61,232.86 | 468.55,366.36 | 461.98,269.71 | 276.23,187.19 | 257.11,200.81 | 209.78,137.04 | | | 10 | 189.03,93.93 | 254.06,347.13 | 204.03,68.67 | 110.11,44.11 | 211.56,101.18 | 129.56,55.63 |
| --- | --- | --- | --- | --- | --- | --- |
| 11 | 242.43,58.49 | 178.81,60.65 | 601.07,651.39 | 358.44,291.53 | 650.83,643.25 | 326.46,275.01 | | 0 |
| Databases | Populationsize | Train/Testsizes | Pre-processing | |
| --- | --- | --- | --- | --- |
| ECG | PTB<br>Capnobase<br>CASIAV1<br>FVC2004-DB3 | 52<br>42<br>108<br>100 | 52*1000/1560*1000<br>42*700/840*700<br>108*4800/756*4800<br>100*6056/800*6056 | FIRfilter,Rpeakdet.,Segmentation<br>Butterworth,Peakdet.,Segmentation<br>Localization<br>Normalization,Orientation |
| PPG | | | | | | | Iris |
| --- |
| Finger | | 1 |
| Databases | Populationsize | Train/Testsizes | Pre-processing | |
| --- | --- | --- | --- | --- |
| ECG | PTB<br>Capnobase<br>CASIAV1<br>FVC2004-DB3 | 52<br>42<br>108<br>100 | 52*1000/1560*1000<br>42*700/840*700<br>108*4800/756*4800<br>100*6056/800*6056 | FIRfilter,Rpeakdet.,Segmentation<br>Butterworth,Peakdet.,Segmentation<br>Localization<br>Normalization,Orientation |
| PPG | | | | | | | UCIDataset | Acronym | Targetclass | #Target | #Non-target | #Params |
| --- | --- | --- | --- | --- | --- |
| Low-dimensional | | | | | |
| Abalone<br>Biomed<br>BreastWisconsin<br>Diabetes(primaindians)<br>Ecoli<br>Iris<br>Liver | AB<br>BI<br>BW<br>D<br>E<br>I<br>L | 1<br>normal<br>benign<br>present<br>pp<br>Iris-setosa<br>healthy | 1407<br>127<br>458<br>500<br>52<br>50<br>200 | 2770<br>67<br>241<br>268<br>284<br>100<br>145 | 10<br>5<br>9<br>8<br>7<br>4<br>6 |
| High-dimensional | | | | | |
| Arrhythmia<br>Breastcancerwisconsin(diagnostic)<br>Breastcancerwisconsin(prognostic)<br>Colon<br>Concordia<br>Sonar<br>Spectf | AR<br>BC-D<br>BC-P<br>C<br>CO<br>S<br>SP | normal<br>B<br>N<br>normal<br>2<br>M<br>0 | 237<br>357<br>151<br>22<br>400<br>111<br>95 | 183<br>212<br>47<br>40<br>3600<br>97<br>254 | 278<br>30<br>33<br>1908<br>1024<br>60<br>44 | | 0 |
| Databases | Populationsize | Train/Testsizes | Pre-processing | |
| --- | --- | --- | --- | --- |
| ECG | PTB<br>Capnobase<br>CASIAV1<br>FVC2004-DB3 | 52<br>42<br>108<br>100 | 52*1000/1560*1000<br>42*700/840*700<br>108*4800/756*4800<br>100*6056/800*6056 | FIRfilter,Rpeakdet.,Segmentation<br>Butterworth,Peakdet.,Segmentation<br>Localization<br>Normalization,Orientation |
| PPG | | | | | | | Iris |
| --- |
| Finger | | 1 |
| Databases | Populationsize | Train/Testsizes | Pre-processing | |
| --- | --- | --- | --- | --- |
| ECG | PTB<br>Capnobase<br>CASIAV1<br>FVC2004-DB3 | 52<br>42<br>108<br>100 | 52*1000/1560*1000<br>42*700/840*700<br>108*4800/756*4800<br>100*6056/800*6056 | FIRfilter,Rpeakdet.,Segmentation<br>Butterworth,Peakdet.,Segmentation<br>Localization<br>Normalization,Orientation |
| PPG | | | | | | | Abalone<br>Biomed<br>BreastWisconsin<br>Diabetes(primaindians)<br>Ecoli<br>Iris<br>Liver | AB<br>BI<br>BW<br>D<br>E<br>I<br>L | 1<br>normal<br>benign<br>present<br>pp<br>Iris-setosa<br>healthy | 1407<br>127<br>458<br>500<br>52<br>50<br>200 | 2770<br>67<br>241<br>268<br>284<br>100<br>145 | 10<br>5<br>9<br>8<br>7<br>4<br>6 |
| --- | --- | --- | --- | --- | --- |
| High-dimensional | | | | | |
| Arrhythmia<br>Breastcancerwisconsin(diagnostic)<br>Breastcancerwisconsin(prognostic)<br>Colon<br>Concordia<br>Sonar<br>Spectf | AR<br>BC-D<br>BC-P<br>C<br>CO<br>S<br>SP | normal<br>B<br>N<br>normal<br>2<br>M<br>0 | 237<br>357<br>151<br>22<br>400<br>111<br>95 | 183<br>212<br>47<br>40<br>3600<br>97<br>254 | 278<br>30<br>33<br>1908<br>1024<br>60<br>44 | | 0 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork | MMParSU |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Random8388607<br>33554431<br>134217727 | 1.3051.267<br>14.88414.574<br>1.1061.052<br>4.7514.653<br>20.94719.971 | 0.5362.40.929<br>3.6144.17.481<br>0.4232.60.608<br>1.2333.94.254<br>4.3024.910.399 | 0.6761.9<br>2.8965.1<br>0.4362.5<br>1.0694.4<br>4.1195.1 |
| 10000000<br>100000000<br>Gauss8388607<br>33554431<br>134217727 | 1.2821.260<br>14.34913.993<br>1.0561.058<br>4.7334.503<br>19.98919.233 | 0.4662.81.092<br>3.4294.29.069<br>0.4072.60.621<br>1.2943.72.840<br>4.8624.19.264 | 0.5682.3<br>2.6995.3<br>0.4062.6<br>1.3683.5<br>4.2794.7 | | | 10000000<br>100000000<br>Buckets8388607<br>33554431<br>134217727 | 1.2901.211<br>14.73214.026<br>1.0710.967<br>4.6694.515<br>20.65519.030 | 0.3443.70.734<br>3.1534.78.399<br>0.3553.01.102<br>1.1384.12.498<br>3.9335.39.265 | 0.7341.8<br>3.0964.8<br>0.5312.0<br>1.2943.6<br>3.8355.4 |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Staggered8388607<br>33554431<br>134217727 | 1.1871.306<br>13.88914.793<br>1.0631.058<br>4.5964.631<br>19.12919.659 | 0.6092.00.762<br>3.8203.66.676<br>0.3992.71.182<br>1.1214.13.654<br>4.6134.110.233 | 0.7321.6<br>3.1174.5<br>0.5751.8<br>1.4053.3<br>3.9554.8 | | 1 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork | MMParSU |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Random8388607<br>33554431<br>134217727 | 1.3051.267<br>14.88414.574<br>1.1061.052<br>4.7514.653<br>20.94719.971 | 0.5362.40.929<br>3.6144.17.481<br>0.4232.60.608<br>1.2333.94.254<br>4.3024.910.399 | 0.6761.9<br>2.8965.1<br>0.4362.5<br>1.0694.4<br>4.1195.1 |
| 10000000<br>100000000<br>Gauss8388607<br>33554431<br>134217727 | 1.2821.260<br>14.34913.993<br>1.0561.058<br>4.7334.503<br>19.98919.233 | 0.4662.81.092<br>3.4294.29.069<br>0.4072.60.621<br>1.2943.72.840<br>4.8624.19.264 | 0.5682.3<br>2.6995.3<br>0.4062.6<br>1.3683.5<br>4.2794.7 | | | TypeSize | Seq/STLSeqQS | ForkSURandfork | MMParSU |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Random8388607<br>33554431<br>134217727 | 1.3051.268<br>14.89014.575<br>1.1061.053<br>4.7514.653<br>20.94819.972 | 0.5812.21.254<br>3.7104.011.836<br>0.4572.41.116<br>1.2913.74.756<br>4.4664.718.034 | 0.7821.7<br>3.1644.7<br>0.5022.2<br>1.2523.8<br>4.4274.7 |
| 10000000<br>100000000<br>Gauss8388607<br>33554431<br>134217727 | 1.2831.260<br>14.35613.994<br>1.0561.058<br>4.7344.503<br>19.99719.244 | 0.5032.61.341<br>3.5404.112.216<br>0.4782.21.055<br>1.3423.54.381<br>5.1603.916.887 | 0.6472.0<br>2.9024.9<br>0.5172.0<br>1.7992.6<br>4.7184.2 |
| 10000000<br>100000000<br>Buckets8388607<br>33554431<br>134217727 | 1.2911.212<br>14.73414.035<br>1.0710.967<br>4.6704.515<br>20.66619.031 | 0.4882.61.272<br>3.4124.313.230<br>0.4032.71.114<br>1.2663.74.265<br>4.3514.715.014 | 0.8211.6<br>3.3554.4<br>0.5831.8<br>1.4973.1<br>4.0465.1 |
| 10000000<br>100000000<br>Staggered8388607<br>33554431<br>134217727 | 1.1871.306<br>13.89714.800<br>1.0641.058<br>4.5974.631<br>19.13319.660 | 0.6311.91.350<br>4.3413.211.857<br>0.4402.41.213<br>1.2163.84.775<br>4.8444.015.354 | 0.8281.4<br>3.5903.9<br>0.6711.6<br>1.6112.9<br>4.3994.3 | | 0 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork | MMParSU |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Random8388607<br>33554431<br>134217727 | 1.3051.267<br>14.88414.574<br>1.1061.052<br>4.7514.653<br>20.94719.971 | 0.5362.40.929<br>3.6144.17.481<br>0.4232.60.608<br>1.2333.94.254<br>4.3024.910.399 | 0.6761.9<br>2.8965.1<br>0.4362.5<br>1.0694.4<br>4.1195.1 |
| 10000000<br>100000000<br>Gauss8388607<br>33554431<br>134217727 | 1.2821.260<br>14.34913.993<br>1.0561.058<br>4.7334.503<br>19.98919.233 | 0.4662.81.092<br>3.4294.29.069<br>0.4072.60.621<br>1.2943.72.840<br>4.8624.19.264 | 0.5682.3<br>2.6995.3<br>0.4062.6<br>1.3683.5<br>4.2794.7 | | | 10000000<br>100000000<br>Buckets8388607<br>33554431<br>134217727 | 1.2901.211<br>14.73214.026<br>1.0710.967<br>4.6694.515<br>20.65519.030 | 0.3443.70.734<br>3.1534.78.399<br>0.3553.01.102<br>1.1384.12.498<br>3.9335.39.265 | 0.7341.8<br>3.0964.8<br>0.5312.0<br>1.2943.6<br>3.8355.4 |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Staggered8388607<br>33554431<br>134217727 | 1.1871.306<br>13.88914.793<br>1.0631.058<br>4.5964.631<br>19.12919.659 | 0.6092.00.762<br>3.8203.66.676<br>0.3992.71.182<br>1.1214.13.654<br>4.6134.110.233 | 0.7321.6<br>3.1174.5<br>0.5751.8<br>1.4053.3<br>3.9554.8 | | 1 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork | MMParSU |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Random8388607<br>33554431<br>134217727 | 1.3051.267<br>14.88414.574<br>1.1061.052<br>4.7514.653<br>20.94719.971 | 0.5362.40.929<br>3.6144.17.481<br>0.4232.60.608<br>1.2333.94.254<br>4.3024.910.399 | 0.6761.9<br>2.8965.1<br>0.4362.5<br>1.0694.4<br>4.1195.1 |
| 10000000<br>100000000<br>Gauss8388607<br>33554431<br>134217727 | 1.2821.260<br>14.34913.993<br>1.0561.058<br>4.7334.503<br>19.98919.233 | 0.4662.81.092<br>3.4294.29.069<br>0.4072.60.621<br>1.2943.72.840<br>4.8624.19.264 | 0.5682.3<br>2.6995.3<br>0.4062.6<br>1.3683.5<br>4.2794.7 | | | 10000000<br>100000000<br>Buckets8388607<br>33554431<br>134217727 | 1.2911.212<br>14.73414.035<br>1.0710.967<br>4.6704.515<br>20.66619.031 | 0.4882.61.272<br>3.4124.313.230<br>0.4032.71.114<br>1.2663.74.265<br>4.3514.715.014 | 0.8211.6<br>3.3554.4<br>0.5831.8<br>1.4973.1<br>4.0465.1 |
| --- | --- | --- | --- |
| 10000000<br>100000000<br>Staggered8388607<br>33554431<br>134217727 | 1.1871.306<br>13.89714.800<br>1.0641.058<br>4.5974.631<br>19.13319.660 | 0.6311.91.350<br>4.3413.211.857<br>0.4402.41.213<br>1.2163.84.775<br>4.8444.015.354 | 0.8281.4<br>3.5903.9<br>0.6711.6<br>1.6112.9<br>4.3994.3 | | 0 |
| Data<br>Set | Repr | Degree<br>timemem | ConComp<br>timemem | PageRank<br>timemem | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| S1 | EXP<br>DEDUP1<br>BMP | 61<br>54<br>50 | 237<br>227<br>134 | 90<br>81<br>82 | 202<br>171<br>72 | 245<br>311<br>256 | 526<br>484<br>156 |
| S2 | EXP<br>DEDUP1<br>BMP | 294<br>335<br>311 | 2,879<br>2,582<br>186 | 498<br>460<br>335 | 2,869<br>2,573<br>163 | 3,287<br>3,049<br>812 | 9,164<br>8,126<br>293 |
| N1 | EXP<br>DEDUP1<br>BMP | 142<br>141<br>131 | 1,109<br>926<br>219 | 241<br>483<br>149 | 1,088<br>901<br>150 | 1,456<br>1,317<br>469 | 3,389<br>2,874<br>377 | | | N2 | EXP<br>DEDUP1<br>BMP | 268<br>312<br>257 | 2,710<br>2,216<br>479 | 593<br>495<br>280 | 2,690<br>2,194<br>347 | 4,493<br>3,726<br>824 | 8,432<br>6,892<br>691 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| IMDB | EXP<br>DEDUP1<br>BMP | 78<br>85<br>146 | 586<br>553<br>952 | 193<br>194<br>291 | 749<br>594<br>1038 | 861<br>802<br>807 | 1178<br>764<br>1185 | | 1 |
| Data<br>Set | Repr | Degree<br>timemem | ConComp<br>timemem | PageRank<br>timemem | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| S1 | EXP<br>DEDUP1<br>BMP | 61<br>54<br>50 | 237<br>227<br>134 | 90<br>81<br>82 | 202<br>171<br>72 | 245<br>311<br>256 | 526<br>484<br>156 |
| S2 | EXP<br>DEDUP1<br>BMP | 294<br>335<br>311 | 2,879<br>2,582<br>186 | 498<br>460<br>335 | 2,869<br>2,573<br>163 | 3,287<br>3,049<br>812 | 9,164<br>8,126<br>293 |
| N1 | EXP<br>DEDUP1<br>BMP | 142<br>141<br>131 | 1,109<br>926<br>219 | 241<br>483<br>149 | 1,088<br>901<br>150 | 1,456<br>1,317<br>469 | 3,389<br>2,874<br>377 | | | AND | inG | Time<br>Node | Time<br>Node | Time<br>Node | Time<br>Node |
| --- | --- | --- | --- | --- | --- |
| 30 | 1000 | 21<br>1415 | 14<br>3312 | 2<br>2052 | 1<br>849 |
| 2000 | 73<br>2919 | 62<br>6949 | 9<br>4946 | 3<br>1576 | |
| 3000 | 157<br>4460 | 144<br>10732 | 20<br>8602 | 7<br>2461 | |
| 50 | 1000 | 17<br>1115 | 9<br>2110 | 12<br>5811 | 7<br>2365 |
| 2000 | 54<br>2215 | 35<br>4110 | 25<br>10319 | 17<br>5022 | |
| 3000 | 112<br>3326 | 82<br>6296 | 42<br>13912 | 35<br>7497 | | | 0 |
| Data<br>Set | Repr | Degree<br>timemem | ConComp<br>timemem | PageRank<br>timemem | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| S1 | EXP<br>DEDUP1<br>BMP | 61<br>54<br>50 | 237<br>227<br>134 | 90<br>81<br>82 | 202<br>171<br>72 | 245<br>311<br>256 | 526<br>484<br>156 |
| S2 | EXP<br>DEDUP1<br>BMP | 294<br>335<br>311 | 2,879<br>2,582<br>186 | 498<br>460<br>335 | 2,869<br>2,573<br>163 | 3,287<br>3,049<br>812 | 9,164<br>8,126<br>293 |
| N1 | EXP<br>DEDUP1<br>BMP | 142<br>141<br>131 | 1,109<br>926<br>219 | 241<br>483<br>149 | 1,088<br>901<br>150 | 1,456<br>1,317<br>469 | 3,389<br>2,874<br>377 | | | N2 | EXP<br>DEDUP1<br>BMP | 268<br>312<br>257 | 2,710<br>2,216<br>479 | 593<br>495<br>280 | 2,690<br>2,194<br>347 | 4,493<br>3,726<br>824 | 8,432<br>6,892<br>691 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| IMDB | EXP<br>DEDUP1<br>BMP | 78<br>85<br>146 | 586<br>553<br>952 | 193<br>194<br>291 | 749<br>594<br>1038 | 861<br>802<br>807 | 1178<br>764<br>1185 | | 1 |
| Data<br>Set | Repr | Degree<br>timemem | ConComp<br>timemem | PageRank<br>timemem | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| S1 | EXP<br>DEDUP1<br>BMP | 61<br>54<br>50 | 237<br>227<br>134 | 90<br>81<br>82 | 202<br>171<br>72 | 245<br>311<br>256 | 526<br>484<br>156 |
| S2 | EXP<br>DEDUP1<br>BMP | 294<br>335<br>311 | 2,879<br>2,582<br>186 | 498<br>460<br>335 | 2,869<br>2,573<br>163 | 3,287<br>3,049<br>812 | 9,164<br>8,126<br>293 |
| N1 | EXP<br>DEDUP1<br>BMP | 142<br>141<br>131 | 1,109<br>926<br>219 | 241<br>483<br>149 | 1,088<br>901<br>150 | 1,456<br>1,317<br>469 | 3,389<br>2,874<br>377 | | | 50 | 1000 | 17<br>1115 | 9<br>2110 | 12<br>5811 | 7<br>2365 |
| --- | --- | --- | --- | --- | --- |
| 2000 | 54<br>2215 | 35<br>4110 | 25<br>10319 | 17<br>5022 | |
| 3000 | 112<br>3326 | 82<br>6296 | 42<br>13912 | 35<br>7497 | | | 0 |
| Adidas | Chanel | Gucci | HH | Lacoste | MK | Nike | Prada | Puma |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 28.6 | 32.9 | 32.8 | 33.9 | 47.1 | 40.4 | 0.5 | 15.0 | 9.5 |
| 7.1 | 9.2 | 3.0 | 0.0 | 10.9 | 13.5 | 0.1 | 0.2 | 9.1 |
| 14.1 | 4.7 | 9.1 | 0.4 | 18.3 | 22.9 | 3.0 | 0.2 | 4.0 | | | 51.9 | 44.8 | 41.1 | 38.1 | 53.3 | 52.5 | 11.8 | 28.9 | 18.4 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 52.7 | 39.9 | 49.7 | 36.5 | 48.4 | 62.7 | 14.8 | 29.8 | 18.6 |
| 25.4 | 11.8 | 4.7 | 0.6 | 17.9 | 44.2 | 1.6 | 0.9 | 15.5 | | 1 |
| Adidas | Chanel | Gucci | HH | Lacoste | MK | Nike | Prada | Puma |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 28.6 | 32.9 | 32.8 | 33.9 | 47.1 | 40.4 | 0.5 | 15.0 | 9.5 |
| 7.1 | 9.2 | 3.0 | 0.0 | 10.9 | 13.5 | 0.1 | 0.2 | 9.1 |
| 14.1 | 4.7 | 9.1 | 0.4 | 18.3 | 22.9 | 3.0 | 0.2 | 4.0 | | | Adidas | Chanel | Gucci | HH | Lacoste | MK | Nike | Prada | Puma |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 15.4<br>52.9 | 4.6<br>40.5 | 7.6<br>46.4 | 0.0<br>27.7 | 9.1<br>53.2 | 0.5<br>48.0 | 9.1<br>12.6 | 4.5<br>25.9 | 9.1<br>17.4 |
| 13.6<br>56.7 | 9.2<br>37.5 | 11.5<br>44.7 | 3.0<br>30.7 | 13.6<br>55.1 | 10.8<br>55.4 | 0.3<br>4.2 | 9.1<br>35.3 | 9.1<br>24.5 |
| 4.6<br>55.7 | 4.6<br>35.3 | 3.0<br>46.3 | 2.3<br>31.2 | 9.1<br>54.7 | 1.2<br>49.0 | 0.0<br>10.6 | 0.0<br>30.6 | 9.1<br>13.2 |
| 3.9<br>58.8 | 1.7<br>34.7 | 9.1<br>44.2 | 0.0<br>35.3 | 9.1<br>47.9 | 3.5<br>55.7 | 0.0<br>6.0 | 0.0<br>24.0 | 9.1<br>16.2 |
| 7.1<br>51.9 | 9.2<br>44.8 | 3.0<br>41.1 | 0.0<br>38.1 | 10.9<br>53.3 | 13.5<br>52.5 | 0.1<br>11.8 | 0.2<br>28.9 | 9.1<br>18.4 | | 0 |
| Adidas | Chanel | Gucci | HH | Lacoste | MK | Nike | Prada | Puma |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 28.6 | 32.9 | 32.8 | 33.9 | 47.1 | 40.4 | 0.5 | 15.0 | 9.5 | | | 7.1 | 9.2 | 3.0 | 0.0 | 10.9 | 13.5 | 0.1 | 0.2 | 9.1 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 14.1 | 4.7 | 9.1 | 0.4 | 18.3 | 22.9 | 3.0 | 0.2 | 4.0 |
| 51.9 | 44.8 | 41.1 | 38.1 | 53.3 | 52.5 | 11.8 | 28.9 | 18.4 |
| 52.7 | 39.9 | 49.7 | 36.5 | 48.4 | 62.7 | 14.8 | 29.8 | 18.6 |
| 25.4 | 11.8 | 4.7 | 0.6 | 17.9 | 44.2 | 1.6 | 0.9 | 15.5 | | 1 |
| Adidas | Chanel | Gucci | HH | Lacoste | MK | Nike | Prada | Puma |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 28.6 | 32.9 | 32.8 | 33.9 | 47.1 | 40.4 | 0.5 | 15.0 | 9.5 | | | 3.9<br>58.8 | 1.7<br>34.7 | 9.1<br>44.2 | 0.0<br>35.3 | 9.1<br>47.9 | 3.5<br>55.7 | 0.0<br>6.0 | 0.0<br>24.0 | 9.1<br>16.2 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 7.1<br>51.9 | 9.2<br>44.8 | 3.0<br>41.1 | 0.0<br>38.1 | 10.9<br>53.3 | 13.5<br>52.5 | 0.1<br>11.8 | 0.2<br>28.9 | 9.1<br>18.4 | | 0 |
| Science | | | |
| --- | --- | --- | --- |
| Language | Positive | Negative | Ambiguous | | | Swedish | 0.14 | 0.19 | 0.67 |
| --- | --- | --- | --- |
| German | 0.65 | 0.16 | 0.19 |
| Italian | 0.53 | 0.25 | 0.22 |
| English | 0.60 | 0.26 | 0.14 |
| Politics | | | |
| Language | Positive | Negative | Ambiguous |
| Swedish | 0.48 | 0.28 | 0.24 |
| German | 0.34 | 0.34 | 0.31 |
| Italian | 0.28 | 0.57 | 0.15 |
| English | 0.37 | 0.31 | 0.32 | | 1 |
| Science | | | |
| --- | --- | --- | --- |
| Language | Positive | Negative | Ambiguous | | | Language | MessageDistribution<br>EmoticonsNoEmoticonsRatioWith | EmoticonDistribution<br>PositiveNegativeAmbiguous | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Swedish | 4064 | 14975 | 0.21 | 0.46 | 0.27 | 0.27 |
| German | 21294 | 54869 | 0.28 | 0.65 | 0.16 | 0.19 |
| Italian | 46931 | 158858 | 0.23 | 0.34 | 0.50 | 0.16 |
| English | 18327 | 75869 | 0.20 | 0.40 | 0.30 | 0.30 | | 0 |
| Science | | | |
| --- | --- | --- | --- |
| Language | Positive | Negative | Ambiguous |
| Swedish | 0.14 | 0.19 | 0.67 |
| German | 0.65 | 0.16 | 0.19 | | | Italian | 0.53 | 0.25 | 0.22 |
| --- | --- | --- | --- |
| English | 0.60 | 0.26 | 0.14 |
| Politics | | | |
| Language | Positive | Negative | Ambiguous |
| Swedish | 0.48 | 0.28 | 0.24 |
| German | 0.34 | 0.34 | 0.31 |
| Italian | 0.28 | 0.57 | 0.15 |
| English | 0.37 | 0.31 | 0.32 | | 1 |
| Science | | | |
| --- | --- | --- | --- |
| Language | Positive | Negative | Ambiguous |
| Swedish | 0.14 | 0.19 | 0.67 |
| German | 0.65 | 0.16 | 0.19 | | | German | 21294 | 54869 | 0.28 | 0.65 | 0.16 | 0.19 |
| --- | --- | --- | --- | --- | --- | --- |
| Italian | 46931 | 158858 | 0.23 | 0.34 | 0.50 | 0.16 |
| English | 18327 | 75869 | 0.20 | 0.40 | 0.30 | 0.30 | | 0 |
| Methods | DiceCoefficient | HausdorffDistance |
| --- | --- | --- |
| k-meansclustering | 0.5249 | 169.745 |
| Meanshiftclustering | 0.3927 | 221.744 | | | DRLSE | 0.7104 | 95.0747 |
| --- | --- | --- |
| GrabCut | 0.8311 | 42.629 |
| MIST | 0.8545 | 34.375 | | 1 |
| Methods | DiceCoefficient | HausdorffDistance |
| --- | --- | --- |
| k-meansclustering | 0.5249 | 169.745 |
| Meanshiftclustering | 0.3927 | 221.744 | | | InitializationMethod | #ofiteration | VPC | VCL | FB | FW |
| --- | --- | --- | --- | --- | --- |
| MacQueen2 | 45 | 0.664 | 0.7455 | 110972.7 | 1224079.7 |
| Faber | 430 | 0.664 | 0.7455 | 101440.4 | 1224079.7 |
| K-Means++ | 37 | 0.616 | 0.7029 | 101440.5 | 1089058.1 |
| K-Means++×10 | 393 | 0.664 | 0.7455 | 101440.4 | 1224073.7 |
| MaxMinLinear | 34 | 0.665 | 0.7458 | 110972.7 | 1224384.8 | | 0 |
| Methods | DiceCoefficient | HausdorffDistance |
| --- | --- | --- |
| k-meansclustering | 0.5249 | 169.745 |
| Meanshiftclustering | 0.3927 | 221.744 |
| DRLSE | 0.7104 | 95.0747 | | | GrabCut | 0.8311 | 42.629 |
| --- | --- | --- |
| MIST | 0.8545 | 34.375 | | 1 |
| Methods | DiceCoefficient | HausdorffDistance |
| --- | --- | --- |
| k-meansclustering | 0.5249 | 169.745 |
| Meanshiftclustering | 0.3927 | 221.744 |
| DRLSE | 0.7104 | 95.0747 | | | K-Means++×10 | 393 | 0.664 | 0.7455 | 101440.4 | 1224073.7 |
| --- | --- | --- | --- | --- | --- |
| MaxMinLinear | 34 | 0.665 | 0.7458 | 110972.7 | 1224384.8 | | 0 |
| ScenarioParameters | Application1 | Application2 |
| --- | --- | --- |
| ChannelCodingRate | 1/3 | |
| QAMModulation | QPSK | 16-QAM |
| FrequencyBandwidth | 5MHz | 10MHz |
| Dataquantization | 10bits | 14bits |
| FrameType | 1OFDMsymbolpilot<br>every10OFDMsymbolsofdata | | | | FPGA | XilinxVirtex-6LX240T |
| --- | --- |
| ClockFrequency | 100MHz | | 1 |
| ScenarioParameters | Application1 | Application2 |
| --- | --- | --- |
| ChannelCodingRate | 1/3 | |
| QAMModulation | QPSK | 16-QAM |
| FrequencyBandwidth | 5MHz | 10MHz |
| Dataquantization | 10bits | 14bits |
| FrameType | 1OFDMsymbolpilot<br>every10OFDMsymbolsofdata | | | | Scenario | Appli.<br>1 | Appli.<br>2 | Appli.<br>3 | Appli.<br>4 |
| --- | --- | --- | --- | --- |
| ChannelCoding | Rate=1/3<br>Codeblocksize=1024 | | | |
| QAMModulation | QPSK | | | |
| (I)FFTSize | 256 | 512 | 1024 | 2048 |
| TXantenna | 2 | | | |
| Dataquantization | 14bits | | | |
| FPGAType | XilinxVirtex-6LX240T | | | |
| ClockFrequency | 50MHz | | | |
| Simulationtime | Generationof5LTEsub-frames | | | | | 0 |
| ScenarioParameters | Application1 | Application2 |
| --- | --- | --- |
| ChannelCodingRate | 1/3 | |
| QAMModulation | QPSK | 16-QAM |
| FrequencyBandwidth | 5MHz | 10MHz |
| Dataquantization | 10bits | 14bits |
| FrameType | 1OFDMsymbolpilot<br>every10OFDMsymbolsofdata | | | | FPGA | XilinxVirtex-6LX240T |
| --- | --- |
| ClockFrequency | 100MHz | | 1 |
| ScenarioParameters | Application1 | Application2 |
| --- | --- | --- |
| ChannelCodingRate | 1/3 | |
| QAMModulation | QPSK | 16-QAM |
| FrequencyBandwidth | 5MHz | 10MHz |
| Dataquantization | 10bits | 14bits |
| FrameType | 1OFDMsymbolpilot<br>every10OFDMsymbolsofdata | | | | FPGAType | XilinxVirtex-6LX240T |
| --- | --- |
| ClockFrequency | 50MHz |
| Simulationtime | Generationof5LTEsub-frames | | 0 |
| Imageprocessing | Numberofexceedencesabovetarget |
| --- | --- |
| Original512x2560imagealgorithm | 90 |
| CSusing256x1280PFCoeffsviaTwISTorthresholding | 10 |
| CSusing128x640PFCoeffsviaTwISTorthresholding | 23 |
| CSusing128x640PFCoeffs;Removegroupsof5 | 14 | | | CSusing64x320PFCoeffsviaTwISTorthresholding | 32 |
| --- | --- |
| CSusing64x320PFCoeffs;Removegroupsof5 | 8 | | 1 |
| Imageprocessing | Numberofexceedencesabovetarget |
| --- | --- |
| Original512x2560imagealgorithm | 90 |
| CSusing256x1280PFCoeffsviaTwISTorthresholding | 10 |
| CSusing128x640PFCoeffsviaTwISTorthresholding | 23 |
| CSusing128x640PFCoeffs;Removegroupsof5 | 14 | | | image | sizer | size(array) | size(mtbdd)<br>(1)(2) |
| --- | --- | --- | --- |
| image0 | 27040000 | 81120 | 5134329 |
| image1 | 1166400 | 3499 | 44615 |
| image2 | 5760000 | 17280 | 801746 |
| image3 | 29160000 | 87480 | 32911635 |
| image4 | 29160000 | 87480 | 6991148 | | 0 |
| Imageprocessing | Numberofexceedencesabovetarget |
| --- | --- |
| Original512x2560imagealgorithm | 90 |
| CSusing256x1280PFCoeffsviaTwISTorthresholding | 10 |
| CSusing128x640PFCoeffsviaTwISTorthresholding | 23 |
| CSusing128x640PFCoeffs;Removegroupsof5 | 14 | | | CSusing64x320PFCoeffsviaTwISTorthresholding | 32 |
| --- | --- |
| CSusing64x320PFCoeffs;Removegroupsof5 | 8 | | 1 |
| Imageprocessing | Numberofexceedencesabovetarget |
| --- | --- |
| Original512x2560imagealgorithm | 90 |
| CSusing256x1280PFCoeffsviaTwISTorthresholding | 10 |
| CSusing128x640PFCoeffsviaTwISTorthresholding | 23 |
| CSusing128x640PFCoeffs;Removegroupsof5 | 14 | | | image1 | 1166400 | 3499 | 44615 |
| --- | --- | --- | --- |
| image2 | 5760000 | 17280 | 801746 |
| image3 | 29160000 | 87480 | 32911635 |
| image4 | 29160000 | 87480 | 6991148 | | 0 |
| Model | Realpurchases | Predictedpurchases |
| --- | --- | --- |
| with12-hourobservationbaseline1 | 129 | 32 |
| with12-hourobservationbaseline2 | 129 | 245 |
| with12-hourobservationSP | 129 | 110 |
| Model | Realpurchases | Predictedpurchases | | | with12-hourobservationbaseline1 | 75 | 28 |
| --- | --- | --- |
| with12-hourobservationbaseline2 | 75 | 147 |
| with12-hourobservationSP | 75 | 110 | | 1 |
| Model | Realpurchases | Predictedpurchases |
| --- | --- | --- |
| with12-hourobservationbaseline1 | 129 | 32 |
| with12-hourobservationbaseline2 | 129 | 245 |
| with12-hourobservationSP | 129 | 110 |
| Model | Realpurchases | Predictedpurchases | | | Algorithms | Realpurchases | Predictedpurchases |
| --- | --- | --- |
| 12-hourobservationbaseline-1 | 251 | 93 |
| 12-hourobservationbaseline-2 | 251 | 482 |
| MLR | 251 | 51 |
| with12-hourobservationSP | 251 | 355 |
| Algorithms | Realpurchases | Predictedpurchases |
| 12-hourobservationbaseline-1 | 384 | 169 |
| 12-hourobservationbaseline-2 | 384 | 714 |
| MLR | 384 | 1,452 |
| with12-hourobservationSP | 384 | 463 | | 0 |
| Model | Realpurchases | Predictedpurchases |
| --- | --- | --- |
| with12-hourobservationbaseline1 | 129 | 32 | | | with12-hourobservationbaseline2 | 129 | 245 |
| --- | --- | --- |
| with12-hourobservationSP | 129 | 110 |
| Model | Realpurchases | Predictedpurchases |
| with12-hourobservationbaseline1 | 75 | 28 |
| with12-hourobservationbaseline2 | 75 | 147 |
| with12-hourobservationSP | 75 | 110 | | 1 |
| Model | Realpurchases | Predictedpurchases |
| --- | --- | --- |
| with12-hourobservationbaseline1 | 129 | 32 | | | 12-hourobservationbaseline-1 | 384 | 169 |
| --- | --- | --- |
| 12-hourobservationbaseline-2 | 384 | 714 |
| MLR | 384 | 1,452 |
| with12-hourobservationSP | 384 | 463 | | 0 |
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