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What is: Displaced Aggregation Units?

SourceSpatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

Displaced Aggregation Unit replaces classic convolution layer in ConvNets with learnable positions of units. This introduces explicit structure of hierarchical compositions and results in several benefits:

  • fully adjustable and learnable receptive fields through spatially-adjustable filter units
  • reduced parameters for spatial coverage efficient inference
  • decupling of the parameters from the receptive field sizes

More information can be found here.