Balanced semisupervised generative adversarial network for damage assessment from low-data imbalanced-class regime

Gao, YQ; Zhai, PY; Mosalam, KM

Mosalam, KM (corresponding author), Univ Calif Berkeley, Dept Civil & Environm Engn, 723 Davis Hall, Berkeley, CA 94720 USA.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2021; 36 (9): 1094

Abstract

In recent years, applying deep learning (DL) to assess structural damages has gained growing popularity in vision-based structural health monitoring (......

Full Text Link