Fig. 1. Optical configuration of structured detected single-pixel imaging

Fig. 2. Framework of the fully convolutional neural network

Fig. 3. Optical-electronical hybrid neural network

Fig. 4. Example of the original training images and corresponding images with random rotation and lateral shift

Fig. 5. Confusion matrix of the classification results on handwritten digit test set (15 kernels)

Fig. 6. 2D convolutional kernel images of the first layer in the fully convolutional neural network

Fig. 7. MNIST test set classification accuracy of networks with different number of convolutional kernels

Fig. 8. Optical system. (a) Experimental setup; (b) Layout of the handwritten digits on disk

Fig. 9. A pair of binarized convolutional kernel images

Fig. 10. Snapshots of digit "5" in motion at different speeds captured by using a camera

Fig. 11. Single-pixel measurements of moving handwritten digits. (a) Single-pixel measurements of handwritten digits passing through the field of view successively in 1.5 s; (b) Partially enlarged view of the single-pixel measurements of the digit "5" in (a); (c) Result of the differential measurement from (b)

Fig. 12. The ten classes and example images in Fashion-MINST dataset

Fig. 13. Fashion-MINST test set classification accuracy of networks with different number of convolutional kernels

Table 1. Experiment classification results of moving handwritten digits

Table 2. Results of different models on MNIST datasets