Mass Spectral Substance Detections Using Long Short-Term Memory Networks

Mass Spectral Substance Detections Using Long Short-Term Memory Networks

In this paper, mass spectral substance detection methods are proposed, which employ long short-term memory (LSTM) recurrent neural networks to classify the mass spectrometry data and can accurately detect chemical substances. As the LSTM has the excellent understanding ability for the historical inf...

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Bibliographic Details
Main Authors: Junxiu Liu, Jinlei Zhang, Yuling Luo, Su Yang, Jinling Wang, Qiang Fu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Mass spectral substance detections
long short-term memory networks
chemometrics
Online Access:https://ieeexplore.ieee.org/document/8606092/

Internet

https://ieeexplore.ieee.org/document/8606092/

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