Resnet in Resnet: Generalizing Residual Architectures
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Abstract
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.
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3Topics & keywords
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Keywords
- Residual neural network
- Residual
- Computer science
- Overhead (engineering)
- Architecture
- State (computer science)
- Dual (grammatical number)
- Parallel computing
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