# Quantum image classification using principal component analysis

Source: [Quantum image classification using principal component analysis](<https://www.sota2.com/research/paper/68fa332f1e209131ce88ddfc>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:53:47.944Z

Authors: Mateusz Ostaszewski, Przemys{\\l}aw Sadowski, Piotr Gawron

Published: 2015-04-02T14:53:51.000Z

## Abstract

We present a novel quantum algorithm for classification of images. The algorithm is constructed using principal component analysis and von Neuman quantum measurements. In order to apply the algorithm we present a new quantum representation of grayscale images.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1504.00580>)

[PDF](<https://arxiv.org/pdf/1504.00580.pdf>)