Application of deep learning methods to LIBS imaging data

IF 3.8 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part B: Atomic Spectroscopy Pub Date : 2025-08-26 DOI:10.1016/j.sab.2025.107315

Javier E. Rinaldi, Andrés Lucía, Carlos Ararat-Ibarguen, C.A. Rinaldi

引用次数: 0

Abstract

This study explores the application of Convolutional Neural Networks (CNNs) to analyze LIBS images for elemental identification in materials such as steel, zirconium, and aluminum. A ResNet-50 architecture was implemented alongside entropy-based preprocessing to enhance feature extraction. The results demonstrate that CNNs efficiently extract complex features and serve as a cost-effective alternative to conventional spectrometric instruments.

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深度学习方法在LIBS成像数据中的应用

本研究探讨了卷积神经网络（cnn）在分析LIBS图像中的应用，用于钢、锆和铝等材料的元素识别。采用ResNet-50架构和基于熵的预处理来增强特征提取。结果表明，cnn可以有效地提取复杂特征，并作为传统光谱仪器的一种经济有效的替代方法。

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

Spectrochimica Acta Part B: Atomic Spectroscopy 物理-光谱学

CiteScore

6.10

自引率

12.10%

发文量

173

审稿时长

81 days

期刊介绍： Spectrochimica Acta Part B: Atomic Spectroscopy, is intended for the rapid publication of both original work and reviews in the following fields: Atomic Emission (AES), Atomic Absorption (AAS) and Atomic Fluorescence (AFS) spectroscopy; Mass Spectrometry (MS) for inorganic analysis covering Spark Source (SS-MS), Inductively Coupled Plasma (ICP-MS), Glow Discharge (GD-MS), and Secondary Ion Mass Spectrometry (SIMS). Laser induced atomic spectroscopy for inorganic analysis, including non-linear optical laser spectroscopy, covering Laser Enhanced Ionization (LEI), Laser Induced Fluorescence (LIF), Resonance Ionization Spectroscopy (RIS) and Resonance Ionization Mass Spectrometry (RIMS); Laser Induced Breakdown Spectroscopy (LIBS); Cavity Ringdown Spectroscopy (CRDS), Laser Ablation Inductively Coupled Plasma Atomic Emission Spectroscopy (LA-ICP-AES) and Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). X-ray spectrometry, X-ray Optics and Microanalysis, including X-ray fluorescence spectrometry (XRF) and related techniques, in particular Total-reflection X-ray Fluorescence Spectrometry (TXRF), and Synchrotron Radiation-excited Total reflection XRF (SR-TXRF). Manuscripts dealing with (i) fundamentals, (ii) methodology development, (iii)instrumentation, and (iv) applications, can be submitted for publication.