Zero-shot learning and its applications from autonomous vehicles to COVID-19 diagnosis: A review

Rezaei, M orcid.org/0000-0003-3892-421X and Shahidi, M (2020) Zero-shot learning and its applications from autonomous vehicles to COVID-19 diagnosis: A review. Intelligence-Based Medicine, 3-4. 100005. ISSN 2666-5212

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 Elsevier B.V. This is an open access article under the terms of the Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0) (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: COVID-19 Pandemic; SARS-CoV-2; Chest X-Ray (CXR); Zero-Shot Learning; Deep Learning; Semantic Embedding; Machine Learning; Autonomous Vehicles; Supervised Annotation
Dates:
  • Published: December 2020
  • Accepted: 24 September 2020
  • Published (online): 2 October 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 01 Dec 2020 11:12
Last Modified: 01 Dec 2020 11:12
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.ibmed.2020.100005

Share / Export

Statistics