Convolutional Neural Networks
Squeeze aggregated excitation network
Introduced by N in Squeeze aggregated excitation networkThis method introduces the aggregated dense block within the squeeze excitation block to enhance representation. The squeeze method compresses the input flow and sends it to excitation with dense layers to regain its shape. The paper introduces multiple dense layers stacked side by side, similar to ResNeXt. This learns global representations from the condensed information which enhances the representational power of the network.
Source: Squeeze aggregated excitation network
Papers
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