21 citations · 43 across the 10 of their papers we have counts for
4 papers
CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation
Weibin Liao, Xuhong Li, Qingzhong Wang +3
While pre-training on object detection tasks, such as Common Objects in Contexts (COCO) [1], could significantly boost the performance of cell segmentation, it still consumes on ma…
MUSCLE: Multi-task Self-supervised Continual Learning to Pre-train Deep Models for X-ray Images of Multiple Body Parts
Weibin Liao, Haoyi Xiong, Qingzhong Wang +6
While self-supervised learning (SSL) algorithms have been widely used to pre-train deep models, few efforts [11] have been done to improve representation learning of X-ray image an…
Doubly Stochastic Models: Learning with Unbiased Label Noises and Inference Stability
Haoyi Xiong, Xuhong Li, Boyang Yu +3
Random label noises (or observational noises) widely exist in practical machine learning settings. While previous studies primarily focus on the affects of label noises to the perf…
Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models
Xuhong Li, Haoyi Xiong, Yi Liu +4
While fine-tuning pre-trained networks has become a popular way to train image segmentation models, such backbone networks for image segmentation are frequently pre-trained using i…