3 citations · 5 across the 4 of their papers we have counts for
4 papers
Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection
Zhijing Wan, Zhixiang Wang, Zheng Wang +2
One-shot subset selection serves as an effective tool to reduce deep learning training costs by identifying an informative data subset based on the information extracted by an info…
Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ Segmentation
Yuran Wang, Zhijing Wan, Yansheng Qiu +1
In the realm of medical image analysis, self-supervised learning (SSL) techniques have emerged to alleviate labeling demands, while still facing the challenge of training data scar…
Contributing Dimension Structure of Deep Feature for Coreset Selection
Zhijing Wan, Zhixiang Wang, Yuran Wang +3
Coreset selection seeks to choose a subset of crucial training samples for efficient learning. It has gained traction in deep learning, particularly with the surge in training data…
A Survey of Dataset Refinement for Problems in Computer Vision Datasets
Zhijing Wan, Zhixiang Wang, CheukTing Chung +1
Large-scale datasets have played a crucial role in the advancement of computer vision. However, they often suffer from problems such as class imbalance, noisy labels, dataset bias,…