A SARS-CoV-2 Microscopic Image Dataset with Ground Truth Images and Visual Features
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Apr 2020.
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Citing papers per year: 2021: 2; 2022: 4.
6 papers.
- 2021Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformercited by 14
- 2021A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approachescited by 12
- 2022IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approachcited by 7
- 2022A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurementscited by 1
- 2022An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism imagescited by 1
- 2022A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortificationcited by 0
- 2022IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach7 Jun 2022
- 2022An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism images4 Apr 2022
- 2022A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements18 Feb 2022
- 2022A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortification14 Feb 2022
- 2021Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformer1 Aug 2021
- 2021A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approaches7 May 2021