Convolutional Neural Networks

DiCENet is a convolutional neural network architecture that utilizes dimensional convolutions (and dimension-wise fusion). The dimension-wise convolutions apply light-weight convolutional filtering across each dimension of the input tensor while dimension-wise fusion efficiently combines these dimension-wise representations; allowing the DiCE Unit in the network to efficiently encode spatial and channel-wise information contained in the input tensor.

Source: DiCENet: Dimension-wise Convolutions for Efficient Networks

Papers


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Components


Component Type
DiCE Unit
Image Model Blocks

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