Dynamic Sparse R-CNN

no code implementations • CVPR 2022 • Qinghang Hong, Fengming Liu, Dong Li, Ji Liu, Lu Tian, Yi Shan

Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features.

object-detection Object Detection

Empirical Quantitative Analysis of COVID-19 Forecasting Models

no code implementations • 1 Oct 2021 • Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda Petzold

In this paper, we perform quantitative analysis of COVID-19 forecasting of confirmed cases and deaths across different regions in the United States with different forecasting horizons, and evaluate the relative impacts of the following three dimensions on the predictive performance (improvement and variation) through different evaluation metrics: model selection, hyperparameter tuning, and the length of time series required for training.

Model Selection Time Series +1

BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients

no code implementations • 19 Mar 2021 • Yun Zhao, Qinghang Hong, Xinlu Zhang, Yu Deng, Yuqing Wang, Linda Petzold

However, there is a lack of deep learning methods that can model the relationship between measurements, clinical notes and mortality outcomes.

Mortality Prediction Survival Analysis

How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment

no code implementations • 22 Sep 2020 • Yun Zhao, Franklin Ly, Qinghang Hong, Zhuowei Cheng, Tyler Santander, Henry T. Yang, Paul K. Hansma, Linda Petzold

Chronic pain is defined as pain that lasts or recurs for more than 3 to 6 months, often long after the injury or illness that initially caused the pain has healed.