A Standard Processing Pipeline for High-accuracy Measurement of Few-shot Regression on Laser Induced Breakdown Spectroscopy
Laser-induced breakdown spectroscopy (LIBS) faces challenges in high-accuracy quantitative measurement under few-shot scenarios due to spectral noise and data scarcity. Traditional preprocessing methods often fail to preserve subtle spectral features or capture nonlinear correlations. This work proposes a standardized processing pipeline integrating diffusion-based denoising, attention-based autoencoder for dimensionality reduction, group shuffling data augmentation, and ordinary least squares regression. The diffusion module employs a 3D UNet architecture to remove spectral noise while preserving essential emission features. The attention-autoencoder captures nonlinear spectral correlati...
| Authors | Hao Li |
|---|---|
| Primary category | cs.LG |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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