2 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
Teach CLIP to Develop a Number Sense for Ordinal Regression
Yao Du, Qiang Zhai, Weihang Dai +1
Ordinal regression is a fundamental problem within the field of computer vision, with customised well-trained models on specific tasks. While pre-trained vision-language models (VL…
Radiomics-Informed Deep Learning for Classification of Atrial Fibrillation Sub-Types from Left-Atrium CT Volumes
Weihang Dai, Xiaomeng Li, Taihui Yu +3
Atrial Fibrillation (AF) is characterized by rapid, irregular heartbeats, and can lead to fatal complications such as heart failure. The disease is divided into two sub-types based…
Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks
Weihang Dai, Xiaomeng Li, Kwang-Ting Cheng
Deep regression is an important problem with numerous applications. These range from computer vision tasks such as age estimation from photographs, to medical tasks such as ejectio…
Cyclical Self-Supervision for Semi-Supervised Ejection Fraction Prediction from Echocardiogram Videos
Weihang Dai, Xiaomeng Li, Xinpeng Ding +1
Left-ventricular ejection fraction (LVEF) is an important indicator of heart failure. Existing methods for LVEF estimation from video require large amounts of annotated data to ach…
Adaptive Contrast for Image Regression in Computer-Aided Disease Assessment
Weihang Dai, Xiaomeng Li, Wan Hang Keith Chiu +2
Image regression tasks for medical applications, such as bone mineral density (BMD) estimation and left-ventricular ejection fraction (LVEF) prediction, play an important role in c…