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3rd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2020
; 12305 LNCS:244-255, 2020.
Article
in English
| Scopus | ID: covidwho-897926
ABSTRACT
SARS-CoV-2 has characteristics of wide contagion and quick propagation velocity. To analyse the visual information of it, we build a SARS-CoV-2 Microscopic Image Dataset (SC2-MID) with 48 electron microscopic images and also prepare their ground truth images. Furthermore, we extract multiple classical features and novel deep learning features to describe the visual information of SARS-CoV-2. Finally, it is proved that the visual features of the SARS-CoV-2 images which are observed under the electron microscopic can be extracted and analysed. © 2020, Springer Nature Switzerland AG.