65 citations · 119 across the 8 of their papers we have counts for
5 papers · 1 filter
PieTrack: An MOT solution based on synthetic data training and self-supervised domain adaptation
Yirui Wang, Shenghua He, Youbao Tang +8
In order to cope with the increasing demand for labeling data and privacy issues with human detection, synthetic data has been used as a substitute and showing promising results in…
Learning Numerical Observers using Unsupervised Domain Adaptation
Shenghua He, Weimin Zhou, Hua Li +1
Medical imaging systems are commonly assessed by use of objective image quality measures. Supervised deep learning methods have been investigated to implement numerical observers f…
Automatic microscopic cell counting by use of deeply-supervised density regression model
Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel +2
Accurately counting cells in microscopic images is important for medical diagnoses and biological studies, but manual cell counting is very tedious, time-consuming, and prone to su…
Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression
Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel +2
Accurate cell counting in microscopic images is important for medical diagnoses and biological studies. However, manual cell counting is very time-consuming, tedious, and prone to…
Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images
Shenghua He, Jie Zheng, Akiko Maehara +4
Optical coherence tomography (OCT) can provide high-resolution cross-sectional images for analyzing superficial plaques in coronary arteries. Commonly, plaque characterization usin…