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Why consider quantum instead classical pattern recognition techniques?
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AI
DOI：10.1016/j.asoc.2024.112096.png)
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Abstract
En 中文
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.
Keywords:
Quantum computing
Quantum machine learning
Quantum datasets
Quantum algorithms
Quantum computing applications
Journal
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6.6
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1.4W
Citations:
4.8W