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IJMLC 2019 Vol.9(3): 334-343 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.3.807

Classification of Viral Hemorrhagic Fever Focusing Ebola and Lassa Fever Using Neural Networks

Nikolai A. K. Steur and Carsten Mueller

Abstract—Despite more than 40 years of experience of dealing with Ebola virus outbreaks and even almost 50 years with Lassa fever virus onsets, these hemorrhagic fevers still remain an omnipresent threat for the human health. One reason for this situation results from the lack of efficient and effective detection equipment for virus recognition and identification. The present paper thematizes the reliable virus cultivation method for classifying pathogens with the aid of electron microscopy and modifies this method by classifying viruses on images through a concepted software component using neural networks.

Index Terms—Ebola, image classification, image preprocessing, Lassa fever, neural networks.

N. A. K. Steur is with the Baden-Wuerttemberg Cooperative State University, BW 74821 Germany (e-mail: nikolai-steur@t-online.de).


Cite: Nikolai A. K. Steur and Carsten Mueller, "Classification of Viral Hemorrhagic Fever Focusing Ebola and Lassa Fever Using Neural Networks," International Journal of Machine Learning and Computing vol. 9, no. 3, pp. 334-343, 2019.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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