Enhanced deep learning algorithm development to detect pain intensity from facial expression images G Bargshady, X Zhou, RC Deo, J Soar, F Whittaker, H Wang Expert systems with applications 149, 113305, 2020 | 126 | 2020 |
Application of CycleGAN and transfer learning techniques for automated detection of COVID-19 using X-ray images G Bargshady, X Zhou, PD Barua, R Gururajan, Y Li, UR Acharya Pattern Recognition Letters 153, 67-74, 2022 | 54 | 2022 |
The effect of information technology on the agility of the supply chain in the Iranian power plant industry G Bargshady, SM Zahraee, M Ahmadi, A Parto Journal of Manufacturing Technology Management 27 (3), 427-442, 2016 | 46 | 2016 |
Ensemble neural network approach detecting pain intensity from facial expressions G Bargshady, X Zhou, RC Deo, J Soar, F Whittaker, H Wang Artificial Intelligence in Medicine 109, 101954, 2020 | 43 | 2020 |
A joint deep neural network model for pain recognition from face G Bargshady, S Jeffrey, Z Xujuan, CD Ravinesh, W Frank, H Wang IEEE 4th International Conference on Computer and Communication Systems, 2019 | 42 | 2019 |
The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space G Bargshady, X Zhou, RC Deo, J Soar, F Whittaker, H Wang Applied Soft Computing 97, 106805, 2020 | 34 | 2020 |
Performance improvement of decision trees for diagnosis of coronary artery disease using multi filtering approach M Abdar, E Nasarian, X Zhou, G Bargshady, VN Wijayaningrum, ... 2019 IEEE 4th International Conference on Computer and Communication Systems …, 2019 | 31 | 2019 |
Business Inteligence Technology Implimentation Readiness Factors G Bargshady, F Alipanah, AW Abdulrazzaq, F Chukwunonso Jurnal Teknologi 68 (3), 7-12, 2014 | 29 | 2014 |
A survey on text classification and its applications X Zhou, R Gururajan, Y Li, R Venkataraman, X Tao, G Bargshady, ... Web intelligence 18 (3), 205-216, 2020 | 25 | 2020 |
The effective factors on user acceptance in mobile business intelligence G Bargshady, K Pourmahdi, P Khodakarami, T Khodadadi, F Alipanah Jurnal Teknologi (Sciences & Engineering) 72 (4), 49-54, 2015 | 17 | 2015 |
Deep learning model for detection of pain intensity from facial expression J Soar, G Bargshady, X Zhou, F Whittaker Smart Homes and Health Telematics, Designing a Better Future: Urban Assisted …, 2018 | 13 | 2018 |
A new deep convolutional neural network model for automated breast Cancer detection X Zhou, Y Li, R Gururajan, G Bargshady, X Tao, R Venkataraman, ... 2020 7th International Conference on Behavioural and Social Computing (BESC …, 2020 | 10 | 2020 |
A case study of predicting banking customers behaviour by using data mining X Zhou, G Bargshady, M Abdar, X Tao, R Gururajan, KC Chan 2019 6th international conference on behavioral, economic and socio-cultural …, 2019 | 7 | 2019 |
Empirical comparison of deep learning models for fNIRS pain decoding R Fernandez Rojas, C Joseph, G Bargshady, KL Ou Frontiers in Neuroinformatics 18, 1320189, 2024 | 1 | 2024 |
Estimating Depression Severity from Long-Sequence Face Videos via an Ensemble Global Diverse Convolutional Model G Bargshady, R Goecke 2023 International Conference on Digital Image Computing: Techniques and …, 2023 | | 2023 |
An Investigation of Video Vision Transformers for Depression Severity Estimation from Facial Video Data G Bargshady, R Goecke Pacific-Rim Symposium on Image and Video Technology, 211-220, 2023 | | 2023 |
Enhanced deep learning predictive modelling approaches for pain intensity recognition from facial expression video images G Bargshady University of Southern Queensland, 2020 | | 2020 |