Shi, Qinfeng

COVID-19 Chest CT Image Segmentation -- A Deep Convolutional Neural Network Solution

Yan, Q., Wang, B., Gong, D., Luo, C., Zhao, W., Shen, J., Shi, Q., Jin, S., Zhang, L., & You, Z. (2020) · arXiv

COVID-19 diagnosis using AIMedical Image Segmentation Techniques

Cited by 109

Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors

Abedin, A., Ehsanpour, M., Shi, Q., Rezatofighi, H., & Ranasinghe, D. C. (2021) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 107

Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables

Varamin, A. A., Abbasnejad, E., Shi, Q., Ranasinghe, D. C., & Rezatofighi, H. (2018) · Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 44

Towards deep clustering of human activities from wearables

Abedin, A., Motlagh, F., Shi, Q., Rezatofighi, H., & Ranasinghe, D. (2020) · Proceedings of the 2020 International Symposium on Wearable Computers

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 27

What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions

Abbasnejad, E., Wu, Q., Shi, Q., & van den Hengel, A. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Speech and dialogue systemsMultimodal Machine Learning Applications

Cited by 16