Resnet in Resnet: Generalizing Residual Architectures
About
Residual networks (ResNets) have recently achieved state-of-the-art on challenging computer vision tasks. We introduce Resnet in Resnet (RiR): a deep dual-stream architecture that generalizes ResNets and standard CNNs and is easily implemented with no computational overhead. RiR consistently improves performance over ResNets, outperforms architectures with similar amounts of augmentation on CIFAR-10, and establishes a new state-of-the-art on CIFAR-100.
Sasha Targ, Diogo Almeida, Kevin Lyman• 2016
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Image Classification | CIFAR-100 (test) | -- | 3518 | |
| Image Classification | CIFAR-10 (test) | -- | 3381 | |
| Sepsis Classification | eICU 24h lead time | AUC69.4 | 13 | |
| Sepsis Classification | eICU 12h lead time | AUC75.6 | 13 | |
| Sepsis Classification | eICU 8h lead time | AUC76.7 | 13 | |
| Sepsis Early Warning | MIMIC 24-hour window IV (test) | AUC65.3 | 13 | |
| Sepsis Early Warning | MIMIC 12-hour window IV (test) | AUC76.3 | 13 | |
| Sepsis Classification | eICU 4h lead time | AUC81.3 | 13 | |
| Sepsis Early Warning | MIMIC 8-hour window IV (test) | AUC77.6 | 13 | |
| Sepsis Early Warning | MIMIC 4-hour window IV (test) | AUC82.9 | 13 |
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