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Why consider quantum instead classical pattern recognition techniques?

delete2024-11-01
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PRE
AI
A
Artur Gomes Barreto
F
F. F. Fanchini
J
João Paulo Papa
V
Victor Hugo C. de Albuquerque *
DOI:10.1016/j.asoc.2024.112096delete
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摘要

摘要

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.
Keyword:
Quantum computing
Quantum machine learning
Quantum datasets
Quantum algorithms
Quantum computing applications

期刊

Applied Soft Computing 封面图
Applied Soft Computing
IF:
6.6
论文数:
1.4W
被引数:
4.8W

机构

U
Universidade Estadual Paulista
学者数:
3.2W
论文数: 2.1W
被引数: 24
U
universidade federal do ceara
学者数:
1.1W
论文数: 6.4K
被引数: 9
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