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英国拉夫堡大学Hui Fang博士学术报告信息

来源: 点击: 时间:2019年12月20日 17:13

报告题目:Applied Artificial Intelligence: the challenges in practices

报告时间:1224日下午14:30

报告地点:校本部计算机楼313

报告人:Hui Fang博士(英国Loughborough University)

Abstract:

Artificial Intelligence (AI) has become the most active research field during this decade. Many algorithms and deep network architectures have been designed and applied in a variety of real-world applications. In specific, the techniques have been widely used in autonomous driving, digital healthcare and precision agriculture. Although the popularity of AI, there are still many unsolved problems to hinder its further development. In this presentation, I will introduce our recent work to formulate problems from real cases and apply different AI algorithms to build innovative products to satisfy the diverse requirements, e.g. seismic data analysis, neurological disease self-assessment and smart vehicle navigation etc. In addition, we will discuss some attempts on analysing neural network architectures and increase the reliability of using them on affordable hardware devices.

Biography

Dr. Hui Fang is with the computer science department, Loughborough University. He received his B.Sc. from University of Science and Technology Beijing (USTB) China, in 2000 and Ph.D. from the University of Bradford, UK, in 2006. Since then, he has carried out research in several world-leading universities, such as University of Oxford and Swansea University. In 2015, he was appointed as a lecturer in Edge Hill University and promoted to senior lecturer in 2017. In 2018, he worked as a senior lecturer in Liverpool John Moores University before moving to Loughborough University.

He has significant experience of using machine learning techniques and visualization methods in a variety of projects, e.g. EU FP6 content-based video analysis, EPSRC face modelling, The Welsh Assembly funded Research Institute of Visual Computing (RIVIC) project and Innovate UK funded seismic data visual bulletin analysis (VBAS) project. His research expertise lies in the areas of computer vision, image/video processing, pattern recognition, machine learning, deep neural networks, data mining, scientific visualization and visual analytics. He has published more than 50 scientific papers in refereed journals and conferences, e.g. IEEE Transactions on visualization and computer graphics, Pattern Recognition, Computer Graphics Forums and IEEE Transactions on Forensics and Security etc. He is an active reviewer for many prestigious conferences and journals, such as IEEE CVPR, BMVC, IEEE TVCG, PR, CVIU, IVC and ESWA.

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