Cargando…
Automatic materials characterization from infrared spectra using convolutional neural networks
Infrared spectroscopy is a ubiquitous technique used to characterize unknown materials in the form of solids, liquids, or gases by identifying the constituent functional groups of molecules through the analysis of obtained spectra. The conventional method of spectral interpretation demands the exper...
Autores principales: | Jung, Guwon, Jung, Son Gyo, Cole, Jacqueline M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055241/ https://www.ncbi.nlm.nih.gov/pubmed/37006683 http://dx.doi.org/10.1039/d2sc05892h |
Ejemplares similares
-
Deeply-recursive convolutional neural network for Raman spectra identification
por: Zhou, Wei, et al.
Publicado: (2022) -
RamanNet: a lightweight convolutional neural network for bacterial identification based on Raman spectra
por: Zhou, Bo, et al.
Publicado: (2022) -
Machine learning material properties from the periodic table using convolutional neural networks
por: Zheng, Xiaolong, et al.
Publicado: (2018) -
Dense Convolutional Neural Network for Identification of Raman Spectra
por: Zhou, Wei, et al.
Publicado: (2023) -
Automatic mandibular canal detection using a deep convolutional neural network
por: Kwak, Gloria Hyunjung, et al.
Publicado: (2020)