# Face identification by means of a neural net classifier

arXiv: https://arxiv.org/abs/2204.00305 · HTML: https://mlsanity.com/paper/2204.00305/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 6 references that are in the map.
- First posted on arXiv 1 Apr 2022.

## Built on by (most cited first, 2 of 2)

- [Face recognition in a transformed domain](https://mlsanity.com/paper/2204.02608/) (2022)
- [Face recognition with small and large size databases](https://mlsanity.com/paper/2204.08468/) (2022)

## Abstract (arXiv)

This paper describes a novel face identification method that combines the eigenfaces theory with the Neural Nets. We use the eigenfaces methodology in order to reduce the dimensionality of the input image, and a neural net classifier that performs the identification process. The method presented recognizes faces in the presence of variations in facial expression, facial details and lighting conditions. A recognition rate of more than 87% has been achieved, while the classical method of Turk and Pentland achieves a 75.5%.