Deep neural network with compound node functioning as a detector and rejecter

A computer system for modifying a base deep neural network, wherein the base deep neural network comprises, prior to modification, an input layer, an output layer, and one or more hidden layers between the input and output layers, and wherein each layer comprises one or more nodes, such that the one or more hidden layer comprise a first hidden layer that comprises a target node, wherein, prior to modification, the target node has inputs from a lower sub-network of the base deep neural network and has one or more base connections to nodes in an upper sub-network of the base deep neural network, and the target node is trained to detect target node patterns in inputs to the target node that activate the target node beyond a target node threshold, the computer system comprising:

• one or more processor cores;
• and
• a memory in communication with the one or more processor cores, wherein the memory stores computer instructions that, when executed by the one or more processor cores, causes the one or more processor cores to:
• replace the target node with a compound node to thereby create a modified base deep neural network, wherein:
• the compound node comprises at least first and second nodes;
• the first node is trained to detect the target node patterns in inputs to the first node and the second node is trained to detect an absence of the target node patterns in inputs to the second node, wherein the first and second nodes are trained to be non-complementary, and
• the one or more processor cores are configured, with the computer instructions, to replace the target node with the compound node by, among other steps:
• connecting the first node to the upper sub-network of the base deep neural network, such that the first node has a weighted connection for each of the one or more base connection that the target node had to the upper sub-network in the base deep neural network;
• and
• connecting the second node to the upper sub-network of the base deep neural network, such that the second node has a weighted connection for each of the one or more base connection that the target node had to the upper sub-network in the base deep neural network;
• and
• after replacing the target node, train the modified base deep neural network.