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@RedditSota
RedditSota authored Nov 11, 2017
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Expand Up @@ -190,51 +190,71 @@ Research Paper | Datasets | Metric | Source Code | Year
<th align="center" width="20%">Source Code</th>
<th align="center" width="10%">Year</th>
</tr>
<tr>
<tr>
<td><a href='https://arxiv.org/pdf/1710.09829.pdf'> Dynamic Routing Between Capsules </a></td>
<td align="left"> <ul><li> MNIST </li></ul></td>
<td align="left"> <ul><li> MNIST </li></ul> </td>
<td align="left"> <ul><li> Test Error: 0.25±0.005 </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/gram-ai/capsule-networks'>PyTorch</a> </li><li> <a href='https://github.com/naturomics/CapsNet-Tensorflow'>Tensorflow</a> </li><li> <a href='https://github.com/XifengGuo/CapsNet-Keras'>Keras</a> </li><li> <a href='https://github.com/soskek/dynamic_routing_between_capsules'>Chainer</a> </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/gram-ai/capsule-networks'>PyTorch</a> </li><li> <a href='https://github.com/naturomics/CapsNet-Tensorflow'>Tensorflow</a> </li><li> <a href='https://github.com/XifengGuo/CapsNet-Keras'>Keras</a> </li><li> <a href='https://github.com/soskek/dynamic_routing_between_capsules'>Chainer</a> </li></ul> </td>
<td align="left">2017</td>
</tr>
<tr>
<tr>
<td><a href='https://arxiv.org/pdf/1102.0183.pdf'> High-Performance Neural Networks for Visual Object Classification </a></td>
<td align="left"> <ul><li> NORB </li></ul></td>
<td align="left"> <ul><li> Test Error: 2.53 ± 0.40 </li></ul> </td>
<td align="left"> <ul><li><a href=''>NOT FOUND</a></ul></li> </td>
<td align="left">2011</td>
</tr>
<tr>
<tr>
<td><a href='https://openreview.net/pdf?id=S1NHaMW0b'>ShakeDrop regularization </a></td>
<td align="left"> <ul><li> CIFAR-10 </li> <li> CIFAR-100</li></ul></td>
<td align="left"> <ul><li> CIFAR-10 </li> <li> CIFAR-100</li></ul></td>
<td align="left"> <ul><li> Test Error: 2.31% </li> <li> Test Error: 12.19% </li></ul> </td>
<td align="left"><ul><li> <a href=''>NOT FOUND</a> </li></ul> </td>
<td align="left"> <ul><li> <a href=''>NOT FOUND</a> </li></ul> </td>
<td align="left">2017</td>
</tr>
<tr>
<tr>
<td><a href='https://arxiv.org/pdf/1611.05431.pdf'>Aggregated Residual Transformations for Deep Neural Networks </a></td>
<td align="left"> <ul><li> CIFAR-10 </li></ul></td>
<td align="left"> <ul><li> Test Error: 3.58% </li></ul> </td>
<td align="left"><ul><li> <a href=''>NOT FOUND</a> </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/facebookresearch/ResNeXt'>PyTorch</a> </li></ul> </td>
<td align="left">2017</td>
</tr>
<tr>
<tr>
<td><a href='https://arxiv.org/pdf/1710.09829.pdf'> Dynamic Routing Between Capsules </a></td>
<td align="left"> <ul><li> MultiMNIST </li></ul></td>
<td align="left"> <ul><li> Test Error: 5% </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/gram-ai/capsule-networks'>PyTorch</a> </li><li> <a href='https://github.com/naturomics/CapsNet-Tensorflow'>Tensorflow</a> </li><li> <a href='https://github.com/XifengGuo/CapsNet-Keras'>Keras</a> </li><li> <a href='https://github.com/soskek/dynamic_routing_between_capsules'>Chainer</a> </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/gram-ai/capsule-networks'>PyTorch</a> </li><li> <a href='https://github.com/naturomics/CapsNet-Tensorflow'>Tensorflow</a> </li><li> <a href='https://github.com/XifengGuo/CapsNet-Keras'>Keras</a> </li><li> <a href='https://github.com/soskek/dynamic_routing_between_capsules'>Chainer</a> </li></ul> </td>
<td align="left">2017</td>
</tr>
<tr>
<tr>
<td><a href='https://arxiv.org/pdf/1611.05431.pdf'>Aggregated Residual Transformations for Deep Neural Networks </a></td>
<td align="left"> <ul><li> ImageNet-1k </li></ul></td>
<td align="left"> <ul><li> Top-1 Error: 20.4% </li></ul> </td>
<td align="left"><ul> <li> <a href='https://github.com/facebookresearch/ResNeXt'>PyTorch</a> </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/facebookresearch/ResNeXt'>PyTorch</a> </li></ul> </td>
<td align="left">2016</td>
</tr>
</tbody>
</table>

#### 2. Instance Segmentation
<table>
<tbody>
<tr>
<th width="30%">Research Paper</th>
<th align="center" width="20%">Datasets</th>
<th align="center" width="20%">Metric</th>
<th align="center" width="20%">Source Code</th>
<th align="center" width="10%">Year</th>
</tr>
<tr>
<td><a href='https://arxiv.org/pdf/1703.06870.pdf'>Mask R-CNN</a></td>
<td align="left"> <ul><li> COCO </li></ul></td>
<td align="left"> <ul><li> Average Precision: 37.1% </li></ul> </td>
<td align="left"> <ul><li> <a href='https://github.com/matterport/Mask_RCNN'>TensorFlow (This is not official. Performance is worse than the reported AP)</a> </li></ul> </td>
<td align="left">2017</td>
</tr>
</tbody>
</table>

### Speech
#### 1. ASR
Research Paper | Datasets | Metric | Source Code | Year
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