Special Issue Call for Paper

Special issue title

Cognitive Vision & Intelligent Computation Approaches for COVID-19

Scope and Topics

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. It has been recognized as a pandemic by the World Health Organization. As of 4th June 2020, there have been over 6.5 million confirmed cases worldwide, with over 3,88K deaths. It is affecting 213 countries and territories around the world. The symptoms of the disease vary from mild to moderate respiratory illness. Older people and those with underlying medical conditions like diabetes, cardiovascular disease, respiratory problems, and cancer are more likely to develop serious illness. So far COVID-19 has claimed many lives across the globe.

There are several research efforts are being made in the area of intelligent computation for the prediction and detection of the growth and trends of COVID-19 along with the need of enhancements.

In recent years, there are several approaches already been proposed to mimic the human intelligence capabilities with the hybridization of prior knowledge and visual information for the cognitive vision. It has the capability of acquiring contextual knowledge from visual experiences also. So, knowledge-based vision systems may integrate the data-driven approaches that perform computer vision tasks through intelligent computation (Artificial Intelligence and Machine Learning Algorithms) offered by prior knowledge into an inference process. So, cognitive vision and intelligent computation may be helpful in the analysis of COVID-19 growth with community behavior. Wrapping this data with artificial intelligence and machine learning algorithms may be helpful in forecasting different aspects related to COVID-19 and its symptom correlation. It is also helpful in epidemiological correlations between different aspects of disease spreading based on the previous history and cognitive mapping of the people during this pandemic.

Specifically, innovative contributions that either solve or advance the understanding of issues related to new technologies and applications in the real world in the direction of cognitive vision and intelligent computation for the prediction and detection of the growth and trends of COVID-19 are very welcome.

Potential topics include, but are not limited to the following:

Symptoms correlation and epidemiologyCognitive vision in growth and trend of COVID-19Cognitive vision approach in early detection of COVID-19Cognitive vision and differential diagnosis Role of cognitive vision and intelligent computing in COVID-19 detection and predictionMachine learning based approaches for monitoring and detection in case of COVID-19Computational correlation in pneumonia and COVID-19COVID-19 detection using deep learning modelsArtificial intelligence-based methods in COVID-19 related data collection and visualizationData mining and knowledge discovery in healthcareDecision support systems for healthcare and wellbeingEvolutionary algorithms for symptoms detection and impact evaluationIntelligent computing platforms Big data and cloud computing frameworks and architectures for applied computationVisualization and interactive interfaces in case of COVID-19Cognitive vison and intelligent hospital managementCognitive-intelligent human behavior mapping of COVID-19 patients

Important Dates

Submissions Deadline: November 10, 2020

First Reviews Due: January 30, 2021

Revision Due: April 15, 2021

Second Reviews Due/Notification: June 15, 2021

Final Manuscript Due: July 15, 2021

Final decisions: July 30, 2021

Guest Editors:

Ashutosh Kumar Dubey, Senior Member (IEEE and ACM), Chitkara University, Punjab, India

Vincenzo Piuri, IEEE Fellow, 2015 IEEE Vice President (Technical Activities), University of Milan, Italy

Sreenatha Anavatti, University of New South Wales (UNSW at Canberra), Australia

Umesh Chandra Pati, Senior Member IEEE, National Institute of Technology, Rourkela, Odisha, India

Ahmed M. Elmisery, Faculty of Computing, Engineering and Science, University of South Wales, United Kingdom

Sam Goundar, British University Vietnam/University of Staffordshire, Hung Yen, Vietnam

Abhishek Kumar, Senior Member IEEE, Chitkara University, Punjab, India