PATCHING DEPLOYED DEEP NEURAL NETWORKS FOR AUTONOMOUS MACHINE APPLICATIONS
In various examples, rapid resolution of deep neural network (DNN) failure modes may be achieved by deploying patch neural networks (PNNs) trained to operate effectively on the failure modes of the DNN. The PNNs may operate on the same or additional data as the DNN, and may generate new signals in a...
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Zusammenfassung: | In various examples, rapid resolution of deep neural network (DNN) failure modes may be achieved by deploying patch neural networks (PNNs) trained to operate effectively on the failure modes of the DNN. The PNNs may operate on the same or additional data as the DNN, and may generate new signals in addition to those generated using the DNN that address the failure modes of the DNN. A fusion mechanism may be employed to determine which output to rely on for a given instance of the DNN/PNN combination. As a result, failure modes of the DNN may be addressed in a timely manner that requires minimal deactivation or downtime for the DNN, a feature controlled using the DNN, and/or semi-autonomous or autonomous functionality as a whole. |
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