Scientists from the Shenzhen Institutes of Advanced Technology adopted finite volume (FV)-LBM to simulate the thermal incompressible flow on unstructured grids, and proposed a parallel coupled cell-centered FV thermal lattice Boltzmann method, which has the potential to simulate flows in complicated domains.
A research team led by Prof. LI Guanglin and Prof. FANG Peng from the Shenzhen Institutes of Advanced Technology proposed an optimized deep learning algorithm for detecting sensory events occurring during stimulation of the nerves using a stretchable and flexible electrocorticography (ECoG) electrode.
Researchers from the Shenzhen Institutes of Advanced Technology proposed a topological analysis framework to characterize the dynamics of the gait fluctuations in different neurodegenerative diseases, which provided a robust qualitative descriptor for the neurodegenerative disease.
A research team led by Dr. ZHANG Qieshi from the Shenzhen Institutes of Advanced Technology has proposed a new technical solution to address the current depth estimation for autonomous driving.
A research team led by Prof. ZHANG Yong from the Shenzhen Institutes of Advanced Technology has addressed the challenge of VNFs by designing a series of efficient algorithms.
A research team led by Prof. ZHOU Yimin from Shenzhen Institutes of Advanced Technology proposed a fast-running human detection system for the UAV based on optical flow and deep convolution networks.
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