
Zhen (Leo) Liu (CEE) is the principal investigator on a project that has received a $227,367 research and development grand from the National Science Foundation.
Shiyan Hu (ECE/MTTI) is Co-PI on the project “Image-Data-Driven Deep Learning in Geosystems.” This is a two-year project.
By Sponsored Programs.
Abstract
Breakthroughs in deep learning in 2006 triggered numerous cutting-edge innovations in text processing, speech recognition, driverless cars, disease diagnosis, and so on. This project will utilize the core concepts underlying the recent computer vision innovations to address a rarely-discussed, yet urgent issue in engineering: how to analyze the explosively increasing image data including images and videos, which are difficult to analyze with traditional methods.
The goal of this study is to understand the image-data-driven deep learning in geosystems with an exploratory investigation into the stability analysis of retaining walls. To achieve the goal, the recent breakthroughs in computer vision, which were later used as one of the core techniques in the development of Google’s AlphaGo, will be studied for its capacity in assessing the stability of a typical geosystem, i.e., retaining walls.










The Vice President for Research Office announced the 2017 REF awards and thanked the volunteer review committees, as well as the deans and department chairs, for their time spent on this important internal research award process.






Ameya Narkar received first prize for his poster presentation at the 2017 Upper Peninsula American Chemical Society Student Research Symposium, which was held Saturday, March 25, 2017, in Marquette.