  This paper presents a technique to measure the gain of a single-plate
micro-channel plate (MCP)/phosphor assembly by using a convolutional neural
network to analyse images of the phosphor screen, recorded by a charge coupled
device. The neural network reduces the background noise in the images
sufficiently that individual electron events can be identified. From the
denoised images, an algorithm determines the average intensity recorded on the
phosphor associated with a single electron hitting the MCP. From this average
single-particle-intensity, along with measurements of the charge of bunches
after amplification by the MCP, we were able to deduce the gain curve of the
MCP.
