Fig. 2: Control program framework and video processing principle.
From: Machine-learning-assisted and real-time-feedback-controlled growth of InAs/GaAs quantum dots

a The framework of the program. An electron beam generated by an electron gun is continuously applied to the rotating substrate, creating a diffraction image frame by frame on the fluorescent screen. Multiple images are then converted to a new matrix, and the reshaped matrix is then transferred to the model for generation of results to guide the adjustment of material growth parameters. b A typical reflection high-energy electron diffraction (RHEED) image taken from the camera and the cropping area. The area marked by the blue square is an effective selection area that the software must handle and subsequently provide as input to the model. c Continuous sampling method for RHEED images. The software processes images with data at position T during each iteration. T is comprised of several sub-images taken sequentially from time t, including t-1, t-2, and so forth. Similarly, the data positions processed by the software in the previous iteration are T-1, T-2, and so on. d Processing method for sampled images. The data at a specific position T is initially acquired. Subsequently, each data point within T, denoted as t, t-1, t-2, and so forth, is transformed into a 2D matrix containing only black and white channels. Finally, these individual 2D matrices are stitched into a 3D matrix.