Muhammad Sohail

Short Bio

Muhammad Sohail is a researcher at FAU within the chair of Digital Reality. Previously, he completed his Bachelor’s studies at the COMSATS Institute of Information Technology, Wah Campus, Pakistan. Afterward, he graduated with a Master’s degree from Shanghai Jiao Tong University, China, where his research was focused on Medical Image Synthesis using Generative Adversarial Networks.

Citation Style:    Display Alpha ACM SIGGRAPH IEEEtran Publications

2020 eXnet: An Efficient Approach for Emotion Recognition in the Wild. Muhammad Naveed Riaz, Yao Shen, Muhammad Sohail, Minyi Guo. Sensors 2020, 20(4), 2020.Muhammad Naveed Riaz, Yao Shen, Muhammad Sohail, and Minyi Guo. exnet: An efficient approach for emotion recognition in the wild. Sensors, 20(4):205–219, February 2020.Naveed Riaz, M., Shen, Y., Sohail, M., and Guo, M. 2020. exnet: An efficient approach for emotion recognition in the wild. Sensors 20, 4 (Feb.), 205–219.M. Naveed Riaz, Y. Shen, M. Sohail, and M. Guo, “exnet: An efficient approach for emotion recognition in the wild,” Sensors, vol. 20, no. 4, pp. 205–219, Feb. 2020. [Web Page][PDF (53 MB)][Low-res PDF (1.1 MB)][BibTeX][DOI]

2019 Unpaired Multi-contrast MR ImageSynthesis Using GenerativeAdversarial Networks. Muhammad Sohail, Muhammad Naveed Riaz, Jing Wu, Chengnian Long, Shaoyuan Li. Simulation and Synthesis in Medical Imaging, 4th International Workshop, SASHIMI 2019, 11827, pp. 22–31, 2019.Muhammad Sohail, Muhammad Naveed Riaz, Jing Wu, Chengnian Long, and Shaoyuan Li. Unpaired multi-contrast mr imagesynthesis using generativeadversarial networks. Simulation and Synthesis in Medical Imaging, 4th International Workshop, SASHIMI 2019, 11827:22–31, October 2019.Sohail, M., Naveed Riaz, M., Wu, J., Long, C., and Li, S. 2019. Unpaired multi-contrast mr imagesynthesis using generativeadversarial networks. Simulation and Synthesis in Medical Imaging, 4th International Workshop, SASHIMI 2019 11827 (Oct.), 22–31.M. Sohail, M. Naveed Riaz, J. Wu, C. Long, and S. Li, “Unpaired multi-contrast mr imagesynthesis using generativeadversarial networks,” Simulation and Synthesis in Medical Imaging, 4th International Workshop, SASHIMI 2019, vol. 11827, pp. 22–31, Oct. 2019. [Web Page][Publisher Page][BibTeX][DOI]