UROP Project Listing System
 
Project Title:
Advanced Landslide identifications, classifications, and prevention in Hong Kong using Deep Learning
Supervisor:WANG Yu-Hsing
Co-Supervisor:-
Quota:5
Project Description:Anticipating the imminent threats of landslip hazards triggered by extreme precipitations brought about by global warming, the HKSAR government intends to upgrade the city's climate resilience. Local real-time monitoring data gathered economically at scale is the key. However, data interpenetration can be the most time consuming endeavor. Hence, we have to use the advanced technology to tackle this long-term issue in Hong Kong. In this project, student will have hands-on experience on applying the cutting-edge Deep Learning algorithms on landslide identifications, classifications, and prevention.
Course type:UROP1000 UROP1100 UROP2100 UROP3100 UROP4100 
Applicant's Roles:To apply the Deep Learning algorithms on landslide identifications, classifications, and prevention. Therefore, students need to have passion on programming. 
Applicant's Learning Objectives:Student will have hands-on experience on applying the cutting-edge Deep Learning algorithms on landslide identifications, classifications, and prevention. 
Complexity of the project:Challenging 
 



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