Hyperspectral unmixing for Raman spectroscopy via physics …
2024年3月7日 · Our results demonstrate that unmixing autoencoders provide improved accuracy, robustness and efficiency compared to standard unmixing methods. We also showcase the applicability of autoencoders to complex biological settings by showing improved biochemical characterization of volumetric Raman imaging data from a monocytic cell.
Hyperspectral unmixing for Raman spectroscopy via physics
Hyperspectral unmixing methods are essential to exploit the capabilities of Raman spectroscopy for nondestructive, unbiased chemical characterization in a wide array of domains, from biology, chemistry, and materials to engineering and environmental science.
Hyperspectral unmixing for Raman spectroscopy via physics …
In this work, we have presented an autoencoder-based methodology for hyperspectral unmixing in Raman spectroscopy, which we validated on a wide array of synthetic and real experimental datasets. Our results demonstrate that autoencoders are adept at handling diverse mixture scenarios and exhibit robustness against data artifacts, offering an ...
[PDF] Hyperspectral unmixing for Raman spectroscopy via …
2024年3月7日 · This work introduces a framework for Raman unmixing based on autoencoder neural networks and demonstrates that such methods offer more versatile, robust, and data-driven Raman unmixing with improved performance compared to conventional methods in complex samples.
Hyperspectral unmixing for Raman spectroscopy via physics …
2024年10月29日 · Our results demonstrate that unmixing autoencoders provide improved accuracy, robustness, and efficiency compared to standard unmixing methods. We also showcase the applicability of...
Hyperspectral Unmixing Based on Multilinear Mixing Model Using ...
2024年1月31日 · In this article, we propose a novel autoencoder (AE)-based network for unsupervised unmixing based on MLM. Leveraging an elaborate network design, this approach explicitly models the relationships among all model parameters: endmembers, abundances, and transition probability.
ICML Hyperspectral Unmixing for Raman Spectroscopy via …
Our results demonstrate that unmixing autoencoders provide improved accuracy, robustness and efficiency compared to standard unmixing methods. We also showcase the applicability of autoencoders to complex biological settings by showing improved biochemical characterization of volumetric Raman imaging data from a human leukemia monocytic cell.
Spectral unmixing and clustering algorithms for assessment of …
2011年6月7日 · In this paper, we compare the chemical and spatial information that can be obtained from a Raman hyperspectral data set using segmentation algorithms and comparing them to spectral unmixing techniques.
Linear unmixing protocol for hyperspectral image fusion analysis ...
2021年9月20日 · In this work, a case study based on the investigation of cross-sections from rice leaves by Raman, synchrotron infrared and fluorescence imaging techniques is presented. HSI of these three...
(PDF) Hyperspectral unmixing for Raman spectroscopy via …
2024年3月7日 · Here, we develop hyperspectral unmixing algorithms based on autoencoder neural networks, and we systematically validate them using both synthetic and experimental benchmark datasets created...