Ghazal Bargshady

Orcid: 0000-0002-2557-7928

Affiliations:
  • University of Southern Queensland, Australia


According to our database1, Ghazal Bargshady authored at least 12 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
An Investigation of Video Vision Transformers for Depression Severity Estimation from Facial Video Data.
Proceedings of the Image and Video Technology - 11th Pacific-Rim Symposium, 2023

Estimating Depression Severity from Long-Sequence Face Videos via an Ensemble Global Diverse Convolutional Model.
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023

2022
Application of CycleGAN and transfer learning techniques for automated detection of COVID-19 using X-ray images.
Pattern Recognit. Lett., 2022

2020
A survey on text classification and its applications.
Web Intell., 2020

Enhanced deep learning algorithm development to detect pain intensity from facial expression images.
Expert Syst. Appl., 2020

The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space.
Appl. Soft Comput., 2020

Ensemble neural network approach detecting pain intensity from facial expressions.
Artif. Intell. Medicine, 2020

A New Deep Convolutional Neural Network Model for Automated Breast Cancer Detection.
Proceedings of the 7th International Conference on Behavioural and Social Computing, 2020

2019
A Joint Deep Neural Network Model for Pain Recognition from Face.
Proceedings of the IEEE 4th International Conference on Computer and Communication Systems, 2019

Performance Improvement of Decision Trees for Diagnosis of Coronary Artery Disease Using Multi Filtering Approach.
Proceedings of the IEEE 4th International Conference on Computer and Communication Systems, 2019

A Case Study of Predicting Banking Customers Behaviour by Using Data Mining.
Proceedings of the 6th International Conference on Behavioral, 2019

2018
Deep Learning Model for Detection of Pain Intensity from Facial Expression.
Proceedings of the Smart Homes and Health Telematics, Designing a Better Future: Urban Assisted Living, 2018


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