Accelerating Deep Neural Networks with Spatial Bottleneck Modules
This paper presents an efficient module named spatial bottleneck for accelerating the convolutional layers in deep neural networks. The core idea is to decompose convolution into two stages, which first reduce the spatial resolution of the feature map, and then restore it to the desired size... (read more)
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Methods used in the Paper
| METHOD | TYPE | |
|---|---|---|
Convolution
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Convolutions |