報告人：劉琳（副教授）
時間：2023.7.28 10:00-11:30
地點：測繪館206會議室
報告人簡介
劉琳，香港中文大學理近20期六合彩結果
地球與環境科學課程副教授、地球與大氣科學研究生學部主任、太空與地球信息科學研究所研究員、能源與可持續發展研究所研究員。主要從事將地球物理、大地測量、深度學習等技術應用于冰凍圈變化研究。2021年獲AGU John Wahr青年科學家獎。
報告簡介
In the era of big data and artificial intelligence, deep learning has emerged as an innovative and important tool in cryosphere remote sensing and modeling and has been applied to nearly all cryospheric components in the Arctic, Antarctica, and high mountain regions. In this talk, I will summarize the exciting and diverse applications of deep learning in cryospheric sciences. Even though most of the published studies in the past five years were demonstrative in nature, these early efforts have successfully proved the effectiveness, robustness, and generalization capability of deep learning in retrieving the patterns of spatial, temporal, and spectral signatures of the cryosphere in remote sensing data, characterizing cryospheric dynamics at local and regional scales, as well as establishing non-linear links between cryospheric processes and various topo-climatic variables.
