Why consider quantum instead classical pattern recognition techniques?

• Published in: Applied soft computing 2024-11, Vol.165, p.112096, Article 112096
• Main Authors: Barreto, Artur Gomes, Fanchini, Felipe Fernandes, Papa, João Paulo, de Albuquerque, Victor Hugo C.
• Format: Article
• Language: English
• Subjects: Quantum algorithms; Quantum computing; Quantum computing applications; Quantum datasets; Quantum machine learning
• ISSN: 1568-4946
• DOI: 10.1016/j.asoc.2024.112096

This article delves into the evolving landscape of pattern recognition, transitioning from classical methodologies to quantum-based techniques. It underscores how quantum algorithms offer a new paradigm with the potential to overcome the limitations of classical techniques. Unlike conventional methods, which, while effective, often struggle with complex and high-dimensional datasets, quantum algorithms are poised to surpass these limitations. This study explores the applications, benefits, drawbacks, and open issues surrounding quantum pattern recognition methods and provides a comprehensive overview of the current state of quantum technology and outlines potential future directions, highlighting the intersection of quantum computing and pattern recognition for breakthroughs. •Comprehensive review of quantum computing to outline the current state of the art.•Comprehensive review of recent advancements in quantum pattern recognition.•Exploration of how quantum datasets can enhance the capabilities of algorithms.•It projects future trends, offering researchers guidance on where to focus efforts.