Abstract
Pattern recognition has been a thriving field of research in many applications, particularly spectral data classification requiring vast, complex, and high-dimensional data. It aims to extract patterns from data and distinguish the acquired data in order to create a new type of description and pattern. This study walks over pattern identification algorithms for spectral data, namely Ultraviolet (UV) and Fourier Transform Infrared (FTIR) especially within the past five years. In addition, this article will address the present trend analysis, obstacles, and future methods for the pattern identification field of research, with a specific emphasis on UV and FTIR spectroscopic data.
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