# Flying By ML -- CNN Inversion of Affine Transforms

arXiv: https://arxiv.org/abs/2312.17258 · HTML: https://mlsanity.com/paper/2312.17258/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 30 references that are in the map.
- First posted on arXiv 22 Dec 2023.

## Builds on (most cited first, 1 of 1)

- [Deep Learning for Image-based Automatic Dial Meter Reading: Dataset and Baselines](https://mlsanity.com/paper/2005.03106/) (2020)

## Abstract (arXiv)

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.