1 code implementation • 7 Nov 2020 • Muhammad Hassan, Yan Wang, Di Wang, Daixi Li, Yanchun Liang, You Zhou, Dong Xu
We collected 100, 000 shoeprints of subjects ranging from 7 to 80 years old and used the data to develop a deep learning end-to-end model ShoeNet to analyze age-related patterns and predict age.