Object recognition devices, electronic devices and methods of recognizing objects
Abstract:
An object recognition device including an artificial neural network (NN) engine configured to receive learning data and weights, make an object recognition model (ORM) learn by using the received information, and provide selected weight data including weights from the selected portion of the weights, and further configured to receive a feature vector, and apply the feature vector extracted from an object data that constructs the object and the selected weight data to the learned ORM to provide an object recognition result, a nonvolatile memory (NVM) configured to store the learned ORM, and an error correction code (ECC) engine configured to perform an ECC encoding on the selected weight data to generate parity data, provide the selected weight data and the parity data to the NVM, and provide the selected weight data to the NN engine by performing an ECC decoding on the selected weight data based on the parity data.
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