Flying By ML -- CNN Inversion of Affine Transforms
L. Van Warren
This paper describes a machine learning method to automate reading of cockpit
gauges, using a CNN to invert affine transformations and deduce aircraft states
from instrument images. Validated with synthetic images of a turn-and-bank
indicator, this research introduces methods such as generating datasets from a
single image, the 'Clean Training Principle' for optimal noise-free training,
and CNN interpolation for continuous value predictions from categorical data.
It also offers insights into hyperparameter optimization and ML system software
engineering.