Oil species identification based on fluorescence excitation-emission matrix and transformer-based deep learning
Authors:
- 26 June 2023
- journal article
- research article
- Published by Elsevier in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
- Vol. 302, 123059
Abstract
No abstract availableKeywords
Funding Information
- Dalian Maritime University
- Key Technologies Research and Development Program (2020YFE0201500)
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities (3132023140)
- Liaoning Revitalization Talents Program (XLYC2001002)
- Dalian High-Level Talent Innovation Program (2022RG02)
This publication has 28 references indexed in Scilit:
- A survey of transfer learningJournal of Big Data, 2016
- Analytical developments for oil spill fingerprintingTrends in Environmental Analytical Chemistry, 2015
- Source identification of sea surface oil with geochemical data in Cantarell, MexicoMicrochemical Journal, 2014
- Review of oil spill remote sensingMarine Pollution Bulletin, 2014
- Characterization of oil components from the Deepwater Horizon oil spill in the Gulf of Mexico using fluorescence EEM and PARAFAC techniquesMarine Chemistry, 2013
- Application of ultraviolet fluorometry and excitation–emission matrix spectroscopy (EEMS) to fingerprint oil and chemically dispersed oil in seawaterMarine Pollution Bulletin, 2008
- Characterisation of middle-distillates by comprehensive two-dimensional gas chromatography (GC×GC): A powerful alternative for performing various standard analysis of middle-distillatesJournal of Chromatography A, 2005
- Characterization and Matching of Oil Samples Using Fluorescence Spectroscopy and Parallel Factor AnalysisAnalytical Chemistry, 2005
- Laser-Induced Fluorescence (LIF) Spectroscopy forIn SituAnalysis of Petroleum Products and Biological Oils in SoilsPolycyclic Aromatic Compounds, 1999
- Long Short-Term MemoryNeural Computation, 1997