Extended Data Fig. 3: An alternative, CNN-Based computing with the memristive SoC for the 32x32 handwritten digits classification. | Nature Sensors

Extended Data Fig. 3: An alternative, CNN-Based computing with the memristive SoC for the 32x32 handwritten digits classification.

From: Event-based neuromorphic sensing system with flexible haptic sensors and a memristive system on a chip

Extended Data Fig. 3

a. For this task we use 2 convolutional layers and 1 fully connected layer structure with 2 max-pooling layers for the reduction of the dimensions. b. Block division of a single 248×256 memristive array for this CNN. c. Target and actual conductance map comparison for the weight mapping of both the convolutional and fully connected layers. d. Accuracy of the writing direction in the digit’s recognition task. We obtain 100% and 99.83% accuracy from the neural network-based computing method from software and hardware results separately.

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