Dr Qingde Li has been a lecturer in computer science at the University of Hull since 2001. Previously he was Professor and Deputy Head of Mathematics and Computer Science at Anhui Normal University, China.
Dr Li's research findings have been published in the world's most prestigious graphics journals including ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics, and IEEE Transactions on Medical Imaging.
Dr Li@Google scholar: https://scholar.google.co.uk/citations?user=abSAMUkAAAAJ&hl=en
High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations
Hong, Q., Li, Q., Wang, B., Tian, J., Xu, F., Liu, K., & Cheng, X. (2020). High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations. Computer Methods and Programs in Biomedicine, 196, https://doi.org/10.1016/j.cmpb.2020.105598
Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality
Bian, W., Xu, D., Cheng, Y., Li, Q., Luo, Y., & Yu, Q. (2020). Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality. IET Biometrics, 9(5), 194-204. https://doi.org/10.1049/iet-bmt.2019.0121
Local keypoint-based Faster R-CNN
Ding, X., Li, Q., Cheng, Y., Wang, J., Bian, W., & Jie, B. (in press). Local keypoint-based Faster R-CNN. Applied Intelligence, https://doi.org/10.1007/s10489-020-01665-9
Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes
Yang, X., Han, X., Li, Q., He, L., Pang, M., & Jia, C. (2020). Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes. IEEE access : practical innovations, open solutions, 8, 40861-40880. https://doi.org/10.1109/access.2020.2976847
Dr Li's current research interests are in the areas of computer graphics, visual and tangible computing, as well as their applications in mixed reality environment , including
(1). High precision geometric reconstruction of vascular and neural structures.
(2). Deep learning on shape understanding and geometric information processing.
(3). Tactile modelling and haptic effects programming.
(4). Environmental geometry-aware wearable devices.
Dr Li welcomes applications in the areas of visual and tangible computing, deep learning in geometric information processing and scientific simulation, cloud-based collaborative geometric design in mixed reality environment, as well as developing environmental geometry-aware wearable devices.