Title: Non-Linear Quantum-Classical Hybrid Algorithm for Image Recognition

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper presents a novel non-linear quantum-classical hybrid algorithm designed for enhanced image recognition performance. The core concept revolves around leveraging the quantum computer's ability to perform intricate feature extraction, coupled with the classical optimizer's capacity for precise refinement and optimization. We address the limitations of traditional approaches by integrating these two paradigms to overcome inherent challenges in image recognition, specifically concerning the representation of complex, non-linear patterns. This research focuses on a specific image recognition task – object classification – and demonstrates the algorithm's effectiveness through rigorous experimentation and analysis. The proposed algorithm offers a potential paradigm shift in image recognition by intelligently combining the speed and computational power of quantum systems with the adaptability of classical optimization. This paper delves into the theoretical underpinnings of the algorithm, details the implementation process, and presents the results of a comprehensive evaluation, emphasizing the algorithm's potential to significantly improve accuracy and efficiency.

DOI: 10.5281/zenodo.22603134

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