| Full text | |
| Author(s): |
Barreto, Artur Gomes
;
Fanchini, Felipe Fernandes
;
Papa, Joao Paulo
;
Albuquerque, Victor Hugo C. de
Total Authors: 4
|
| Document type: | Journal article |
| Source: | APPLIED SOFT COMPUTING; v. 165, p. 11-pg., 2024-08-21. |
| Abstract | |
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. (AU) | |
| FAPESP's process: | 23/14427-8 - Data Science for Smart Industry (CDII) |
| Grantee: | José Alberto Cuminato |
| Support Opportunities: | Research Grants - Research Centers in Engineering Program |
| FAPESP's process: | 23/04987-6 - Quantum optimization and machine learning: variational algorithms and applications |
| Grantee: | Felipe Fernandes Fanchini |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 23/12830-0 - Quantum Intelligent Systems for Cybersecurity |
| Grantee: | Kelton Augusto Pontara da Costa |
| Support Opportunities: | Regular Research Grants |