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Analysis of adulterated milk based on a long short-term memory network

  • Published:2023-04-03 Issue:4 Volume:56 Page:204-210
  • ISSN:0038-7010
  • Container-title:Spectroscopy Letters
  • language:en
  • Short-container-title:Spectroscopy Letters

Author:

Li Xin1,Liu Jiangping12

Affiliation:

1. College of Computer and Information Engineering of the Inner Mongolia Agricultural University, Hohhot, China

2. Inner Mongolia Autonomous Region Key Laboratory of Big Data Research and Application of Agriculture and Animal Husbandry, Hohhot, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Inner Mongolia Autonomous Region

Key Technology Research Project of Inner Mongolia Science and Technology Department

Publisher

Informa UK Limited

Subject

Spectroscopy,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Implementing Long Short-Term Memory Network for Enhancing Hyper Spectral Time Series Modeling;2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario (ICPSITIAGS);2023-12-28

2. Food adulteration identification framework via unsupervised Anomaly Detection algorithm: applied to camel milk (FIAD）;Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023);2023-10-10
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