Deep Convolutional Neural Networks

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As of Version 8.0, Backpropagation (see Backprop 8.0 Update) contains support for main features of Deep Convolutional Neural Networks (DCNN's) which have been widely used in a number of different pattern recognition applications (e.g., the now-classic AlexNet model: )

  • The "dropout" regularizer has been added -- see this paper for full details:
  • There is a MAX_POOL act_fun option which computes the max over all of its recv connections, and only backpropagates error back to that max connection.
  • Connection weights can be shared across units, to support convolutional networks. This is supported in the TiledGpRFPrjnSpec ProjectionSpec which creates appropriate overlapping tiled connectivity patterns -- click the share_cons flag.

See our CCN repository here: for downloadable DCNN models.