RADAR: Raman Spectral Analysis Using Deep Learning for Artifact Removal (Advanced Optical Materials 25/2025)

IF 7.2 2区材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY

Advanced Optical Materials Pub Date : 2025-09-03 DOI:10.1002/adom.70254

Joel Sjöberg, Nicoleta Siminea, Andrei Păun, Adrian Lita, Mioara Larion, Ion Petre

引用次数: 0

Abstract

Raman Spectroscopy

In article 10.1002/adom.202500736, Ion Petre and co-workers introduce RADAR, two lightweight deep learning models that simultaneously denoise and correct Raman spectra, reducing data acquisition time by up to 90% while preserving signal integrity. By streamlining artifact removal, RADAR enhances the speed, accuracy, and usability of Raman spectroscopy across diverse applications in materials science, biomedical research, and beyond.

Abstract Image

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RADAR：利用深度学习进行伪影去除的拉曼光谱分析（Advanced Optical Materials 25/2025）

拉曼光谱[j] .文献10.1002/adom。202500736， Ion Petre及其同事介绍了RADAR，这是两种轻量级深度学习模型，可同时对拉曼光谱进行降噪和校正，在保持信号完整性的同时将数据采集时间缩短了90%。通过简化工件去除，RADAR提高了拉曼光谱在材料科学，生物医学研究等各种应用中的速度，准确性和可用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advanced Optical Materials MATERIALS SCIENCE, MULTIDISCIPLINARY-OPTICS

CiteScore

13.70

自引率

6.70%

发文量

883

审稿时长

1.5 months

期刊介绍： Advanced Optical Materials, part of the esteemed Advanced portfolio, is a unique materials science journal concentrating on all facets of light-matter interactions. For over a decade, it has been the preferred optical materials journal for significant discoveries in photonics, plasmonics, metamaterials, and more. The Advanced portfolio from Wiley is a collection of globally respected, high-impact journals that disseminate the best science from established and emerging researchers, aiding them in fulfilling their mission and amplifying the reach of their scientific discoveries.