Interpretability in near-infrared (NIR) spectroscopy: Current pathways to the long-standing challenge

2025/08/01 by Krzysztof B. Beć, Justyna Grabska, Christian W. Huck · 2 citations

paper · doi:10.1016/j.trac.2025.118254

Citations

• Deep learning for near-infrared spectral data modelling: Hypes and benefits
• META-PLS modelling: An integrated approach to automatic model optimization for near-infrared spectra
• Mitigating the Multicollinearity Problem and Its Machine Learning Approach: A Review
• Explainable Predictive Modeling for Limited Spectral Data
• Principles and Applications of Miniaturized Near‐Infrared (NIR) Spectrometers
• Techniques for Interpretable Machine Learning
• Aiming at an accurate prediction of vibrational and electronic spectra for medium‐to‐large molecules: An overview
• Review of the most common pre-processing techniques for near-infrared spectra

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