Publication detail

Deep Learning-based Classification of Viruses Using Transmission Electron Microscopy Images

ALI, M. JOSHI, R. DUTTA, M. BURGET, R. MEZINA, A.

Original Title

Deep Learning-based Classification of Viruses Using Transmission Electron Microscopy Images

Type

conference paper

Language

English

Original Abstract

Humans have a strong urge to categorize natural organisms, and the categorization of viruses becomes more challenging. Viruses are not visible with the naked eyes, and their automatic classification based on images obtained with Transmission Electron Microscopy (TEM) can help a lot in the medical field. Their classification is more challenging due to their complicated intracellular structures and lighting conditions to capture the TEM images. The proposed architecture has been developed for the classification of the 14 different types of viruses. The dataset has been split into the training set, validation set and test set. The proposed model obtained better experimental results with 96.90% classification accuracy on the validation set and 96.10 % on the test set of unseen images. The performance of the proposed model has been compared with state-of-the-art pre-trained deep-learning models such that XceptionNet, MobileNet and DenseNet201. The model is accurate and computationally less complex, which supports faster processing suitable for microscopic cell image analysis for different medical applications.

Keywords

Deep learning; Diagnostic systems; Electron microscopy; Neural Networks; Virus classification.

Authors

ALI, M.; JOSHI, R.; DUTTA, M.; BURGET, R.; MEZINA, A.

Released

15. 7. 2022

Publisher

IEEE

ISBN

978-1-6654-6948-7

Book

45th International Conference on Telecommunications and Signal Processing (TSP 2022). IEEE, 2022

Pages from

174

Pages to

178

Pages count

5

URL

BibTex

@inproceedings{BUT180406,
  author="Mohd Mohsin {Ali} and Rakesh Chandra {Joshi} and Malay Kishore {Dutta} and Radim {Burget} and Anzhelika {Mezina}",
  title="Deep Learning-based Classification of Viruses Using Transmission Electron Microscopy Images",
  booktitle="45th International Conference on Telecommunications and Signal Processing (TSP 2022). IEEE, 2022",
  year="2022",
  pages="174--178",
  publisher="IEEE",
  doi="10.1109/TSP55681.2022.9851305",
  isbn="978-1-6654-6948-7",
  url="https://ieeexplore.ieee.org/abstract/document/9851305"
}