Multi-size convolutional layer
Abstract:
Improved convolutional layers for neural networks can obtain an input feature map comprising groups of channels. Each group of channels can include one or more channels having a predetermined size. The predetermined sizes can differ between the groups. The convolutional layer can generate, for each one of the groups of channels, an output channel. Generation of the output channel can include resizing the channels in the remaining groups of channels to match the predetermined size of the each one of the groups of channels. Generation can further include combining the channels in the each one of the groups with the resized channels and applying the combined channels to a convolutional sub-layer to generate the output channel.
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