Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
This paper explores how well deep learning models trained on chest CT images can diagnose COVID-19 infected people in a fast and automated process. To this end, we adopted advanced deep network architectures and proposed a transfer learning strategy using custom-sized input tailored for each deep ar...
Main Authors: | Hammam Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-01-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/2/455 |
Similar Items
-
COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans
by: Hammam Alshazly, et al.
Published: (2021-07-01) -
Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition
by: Hammam Alshazly, et al.
Published: (2019-09-01) -
Deep Convolutional Neural Networks for Unconstrained Ear Recognition
by: Hammam Alshazly, et al.
Published: (2020-01-01) -
Towards Explainable Ear Recognition Systems Using Deep Residual Networks
by: Hammam Alshazly, et al.
Published: (2021-01-01) -
Explainable Deep Learning Models in Medical Image Analysis
by: Amitojdeep Singh, et al.
Published: (2020-06-01)