This study developed a transformer-based AI model using UAV multispectral and RGB imaging to predict wheat yields with ...

A research team has developed a new artificial intelligence (AI) model that harnesses unmanned aerial vehicle (UAV) data to ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

Liang Hu, Yuanyuan Pei, Xiaojin Luo, Lijuan Wen, Hui Xiao, Jinxing Liu, Liping Wu, Gaochi Li, Fengxiang Wei, A multivariate modeling method for the prediction of low fetal fraction before noninvasive ...

Summary: A new AI framework can detect neurological disorders by analyzing speech with over 90% accuracy. The model, called CTCAIT, captures subtle patterns in voice that may indicate early symptoms ...

In order to investigate the multivariate spatial dependence properties of air pollution extremes, we introduce a new class of multivariate max-stable processes. Our proposed model admits a ...

Then, logistic regression modeled disease status as a function of each marker for different timepoints and multivariate modeling was performed via logistic LASSO regression.

His research interests include multivariate statistical process monitoring, multivariate modeling, and interdisciplinary applications. His previous research focused on applications to pilot water ...