Cited by
Cited by
A computer vision based method for 3D posture estimation of symmetrical lifting
R Mehrizi, X Peng, X Xu, S Zhang, D Metaxas, K Li
Journal of biomechanics 69, 40-46, 2018
Toward marker-free 3D pose estimation in lifting: A deep multi-view solution
R Mehrizi, X Peng, Z Tang, X Xu, D Metaxas, K Li
2018 13th IEEE international conference on automatic face & gesture …, 2018
Using a marker-less method for estimating L5/S1 moments during symmetrical lifting
R Mehrizi, X Xu, S Zhang, V Pavlovic, D Metaxas, K Li
Applied ergonomics 65, 541-550, 2017
Predicting 3-D lower back joint load in lifting: A deep pose estimation approach
R Mehrizi, X Peng, DN Metaxas, X Xu, S Zhang, K Li
IEEE Transactions on Human-Machine Systems 49 (1), 85-94, 2019
A Deep Neural Network-based method for estimation of 3D lifting motions
R Mehrizi, X Peng, X Xu, S Zhang, K Li
Journal of biomechanics 84, 87-93, 2019
New technologies in human factors and ergonomics research and practice
JH Lin, A Kirlik, X Xu
Applied ergonomics 66, 179-181, 2018
Automatic health problem detection from gait videos using deep neural networks
R Mehrizi, X Peng, S Zhang, R Liao, K Li
arXiv preprint arXiv:1906.01480, 2019
Machine Learning Algorithm That Does Not Use Chest Radiograph Data Can Identify Patients with ARDS
MNG J. Chen, R. Mehrizi, B. Aasman, C. Nelapatla, P. Mirhaji, Y. Tang, V ...
American Thoracic Society International Conference 201, 2020
Deep Neural Networks for Human Motion Analysis in Biomechanics Applications
R Mehrizi
Rutgers The State University of New Jersey, School of Graduate Studies, 2019
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