Convolutions

1x1 Convolution

Introduced by Lin et al. in Network In Network

A 1 x 1 Convolution is a convolution with some special properties in that it can be used for dimensionality reduction, efficient low dimensional embeddings, and applying non-linearity after convolutions. It maps an input pixel with all its channels to an output pixel which can be squeezed to a desired output depth. It can be viewed as an MLP looking at a particular pixel location.

Image Credit: http://deeplearning.ai

Source: Network In Network

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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