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. Author manuscript; available in PMC: 2024 Apr 20.
Published in final edited form as: Nat Nanotechnol. 2024 Jan 4;19(4):471–478. doi: 10.1038/s41565-023-01557-2

Fig. 5 |. Classification of MNIST and Fashion MNIST objects.

Fig. 5 |

a, An input image from the MNIST dataset. b, Ideal and experimentally measured feature maps corresponding to the convolution of the data in a with channels 9 and 12. The top-left corner label indicates the channel number during convolution. c, Comparison between the theoretical and measured confusion matrices for MNIST classification. d, An input image from the Fashion MNIST dataset. The top-left corner label indicates the object class number. e, Ideal and experimentally measured feature maps corresponding to the convolution of the data in d with channels 9 and 12. The top-left corner label indicates the channel number during convolution. f, Comparison between the theoretical and measured confusion matrices for Fashion MNIST classification. g, Predicted accuracy curve for the MNIST dataset and the areal density of the basic computing unit as a function of pixel size. The insets depict the kernel profiles and feature maps at different pixel sizes.