Attention-based multimodal fusion of event-reconstructed images and LIBS spectra using CNN and BiLSTM for metal classification

This study introduces dynamic vision sensors (DVS) in LIBS for the first time, and a temporal–spatial attention fusion network is proposed to extract and cross-modally fuse features from LIBS spectral data and plasma images.

Authors

Xilin Wang (ORCID: https://orcid.org/0000-0002-5285-365X)
Lei Deng (ORCID: https://orcid.org/0000-0003-2647-4610)
Zhidong Jia (ORCID: https://orcid.org/0000-0003-1253-4459)
Zikui Shen (ORCID: https://orcid.org/0000-0002-3326-629X)
Jun Wang (ORCID: https://orcid.org/0000-0003-1699-3687)
Honglin Jian

Institutions

China National Electric Apparatus Research Institute (China) (CN)
Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
South China University of Technology (CN)
Tsinghua University (CN)

Publication Details

Journal: Journal of Analytical Atomic Spectrometry
Published: 2025-01-01
DOI: https://doi.org/10.1039/d5ja00238a
Citations: 2
Primary Topic: Laser-induced spectroscopy and plasma
Type: article
Field-Weighted Citation Impact: 1.73

Funders

National Natural Science Foundation of China
Shenzhen International Cooperation Research Project
Basic and Applied Basic Research Foundation of Guangdong Province

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article

Attention-based multimodal fusion of event-reconstructed images and LIBS spectra using CNN and BiLSTM for metal classification

Xilin Wang, Lei Deng, Zhidong Jia, Zikui Shen et al.

Jan 1, 2025

2 citations

Journal of Analytical Atomic Spectrometry

Laser-induced spectroscopy and plasma

1.73

article

Attention-based multimodal fusion of event-reconstructed images and LIBS spectra using CNN and BiLSTM for metal classification

Xilin Wang, Lei Deng, Zhidong Jia, Zikui Shen, Jun Wang, Honglin Jian

January 1, 2025article en

2 citations

Abstract

This study introduces dynamic vision sensors (DVS) in LIBS for the first time, and a temporal–spatial attention fusion network is proposed to extract and cross-modally fuse features from LIBS spectral data and plasma images.

Journal of Analytical Atomic SpectrometryVol. 40(10)

China National Electric Apparatus Research Institute (China) (CN), Shanghai Center for Brain Science and Brain-Inspired Technology (CN), South China University of Technology (CN), Tsinghua University (CN)

National Natural Science Foundation of China, Shenzhen International Cooperation Research Project, Basic and Applied Basic Research Foundation of Guangdong Province

Openalex Percentile: Top 16%

Laser-induced spectroscopy and plasma

1.73

DOI Source OpenAlex

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Attention-based multimodal fusion of event-reconstructed images and LIBS spectra using CNN and BiLSTM for metal classification — Xilin Wang, Lei Deng, et al. · Journal of Analytical Atomic Spectrometry (2025) | TGRS Research Map | TGRS