报告地点：Zoom(ID:724-620-904)
报告时间：2020-06-05 从 15:00 到 16:30
报告人：刘琳
报告人简介：
Lin Liu is an Associate Professor of Earth System Science and head of the Graduate Division of Earth and Atmospheric Science at The Chinese University of Hong Kong (CUHK). He studied at Wuhan University for his bachelor's degree and got his Ph.D. in Geophysics from the University of Colorado at Boulder. Before joining CUHK in 2014, he was a George Thompson Postdoc Fellow at Stanford University. His research applies a wide range of geodetic, geophysical, remote sensing, and machine learning techniques to the cryospheric systems, including permafrost, glaciers, and ice sheets, aiming to quantify and understand their changes in a warming climate. Please visit his webpage https://cryocuhk.github.io for detailed information.
报告题目：How AI can be used to do cold geosciences? - A review of Deep Learning for cryospheric studies
报告内容简介
The cryosphere, Earth’s surface where water is frozen, has been undergoing strong warming and area reduction and casting substantial impacts on the global climate system and socio-economical development. This talk reviews the use of deep learning for cryospheric studies, aiming to showcase the diverse applications of deep learning for tackling research tasks that are becoming more challenging to conventional approaches. Even though such applications are still in an early stage, deep learning has been utilized to characterize nearly all the cryospheric components in a diverse manner. I will give two examples to illustrate how our research group utilizes state-of-the-art deep learning algorithms in the processing of remote sensing imagery towards automated detection of fast changes in glaciers and frozen ground. Finally, I will offer some thoughts on common strengths and limitations as well as future directions of deep-learning-based cryospheric studies.