Recent progress and applications of Raman spectrum denoising algorithms in chemical and biological analyses: A review
Raman spectroscopy is a powerful technique widely used in analytical chemistry. However,
spectral noise emerging during detection introduces potential to compromise the signal-to …
spectral noise emerging during detection introduces potential to compromise the signal-to …
Deep learning in spectral analysis: Modeling and imaging
Deep learning (DL) is powerful to find patterns or hidden information from data using neural
networks. With the growth of data and computing capabilities, DL has rapidly advanced and …
networks. With the growth of data and computing capabilities, DL has rapidly advanced and …
Raman spectroscopy-based microfluidic platforms: A promising tool for detection of foodborne pathogens in food products
Rapid and sensitive detection of foodborne pathogens in food products is paramount for
ensuring food safety and public health. In the ongoing effort to tackle this issue, detection …
ensuring food safety and public health. In the ongoing effort to tackle this issue, detection …
Distributed Raman spectrum data augmentation system using federated learning with deep generative models
Y Kim, W Lee - Sensors, 2022 - mdpi.com
Chemical agents are one of the major threats to soldiers in modern warfare, so it is so
important to detect chemical agents rapidly and accurately on battlefields. Raman …
important to detect chemical agents rapidly and accurately on battlefields. Raman …
Data augmentation using continuous conditional generative adversarial networks for regression and its application to improved spectral sensing
Y Zhu, H Su, P Xu, Y Xu, Y Wang, CH Dong, J Lu… - Optics …, 2023 - opg.optica.org
Machine learning-assisted spectroscopy analysis faces a prominent constraint in the form of
insufficient spectral samples, which hinders its effectiveness. Meanwhile, there is a lack of …
insufficient spectral samples, which hinders its effectiveness. Meanwhile, there is a lack of …
Unsupervised denoising of Raman spectra with cycle-consistent generative adversarial networks
C Bench, MS Bergholt, MA al-Badri - arXiv preprint arXiv:2307.00513, 2023 - arxiv.org
Raman spectroscopy can provide insight into the molecular composition of cells and tissue.
Consequently, it can be used as a powerful diagnostic tool, eg to help identify changes in …
Consequently, it can be used as a powerful diagnostic tool, eg to help identify changes in …
Application of spectral small-sample data combined with a method of spectral data augmentation fusion (SDA-Fusion) in cancer diagnosis
X Zhang, H Li, X Tian, C Chen, Y Su, M Li, J Lv… - Chemometrics and …, 2022 - Elsevier
Background Cancer is one of the most life-threatening diseases to human life, whose
accurate diagnosis is the prerequisite for precise treatment. The detection technology with …
accurate diagnosis is the prerequisite for precise treatment. The detection technology with …
Fragment-Fusion Transformer: Deep Learning-Based Discretization Method for Continuous Single-Cell Raman Spectral Analysis
Q Yu, X Shen, LL Yi, M Liang, G Li, Z Guan, X Wu… - ACS …, 2024 - ACS Publications
Raman spectroscopy has become an important single-cell analysis tool for monitoring
biochemical changes at the cellular level. However, Raman spectral data, typically …
biochemical changes at the cellular level. However, Raman spectral data, typically …
Enhancing glucose classification in continuous flow hydrothermal biomass liquefaction streams through generative AI and IR spectroscopy
Energy from fossil fuels is forecasted to contribute to 28% of the energy demand by 2050.
Shifting to renewable, green energy is desirable to mitigate the adverse effects on the …
Shifting to renewable, green energy is desirable to mitigate the adverse effects on the …
Generative adversarial networks‐based super‐resolution algorithm enables high signal‐to‐noise ratio spatial heterodyne Raman spectra
L Hu, J Shen, Z Chen, Y Zhang… - Journal of Raman …, 2023 - Wiley Online Library
High‐resolution interference pattern images are vital for spatial heterodyne Raman
spectroscopy to produce quality Raman spectra with a good signal‐to‐noise ratio. A sought …
spectroscopy to produce quality Raman spectra with a good signal‐to‐noise ratio. A sought …