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IEEE International Conference on Quantum Computing and Engineering (QCE)

piQture: A QML Library for Image Processing

Saasha Joshi, Daniel Justice, Ulrike Stege

Published Sep 15, 2024• 3 citations
Publisher

Abstract

Quantum Machine Learning (QML) leverages quantum mechanical properties to enhance computational capabilities. With its emergence, there is a need to integrate QML models into machine learning pipelines for real-life applications such as image processing. While standalone programs exist to demonstrate the performance of QML models, a well-defined model workflow is noticeably absent. We present piQture, an open-source Python and Qiskit-based library that streamlines the implementation and training of QML models tailored for image processing. Its design and structure prioritize usability among users familiar with classical machine learning without prior QML experience.

DOI
10.1109/qce60285.2024.10416

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