7 citations · 27 across the 14 of their papers we have counts for
5 papers · 1 filter
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images
Jiawei Yang, Hanbo Chen, Yuan Liang +3
Detectingandsegmentingobjectswithinwholeslideimagesis essential in computational pathology workflow. Self-supervised learning (SSL) is appealing to such annotation-heavy tasks. Des…
TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
Jiawei Yang, Yao Zhang, Yuan Liang +3
Deep learning models are notoriously data-hungry. Thus, there is an urging need for data-efficient techniques in medical image analysis, where well-annotated data are costly and ti…
Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation
Yuan Liang, Weinan Song, Jiawei Yang +3
Convolutional networks (ConvNets) have achieved promising accuracy for various anatomical segmentation tasks. Despite the success, these methods can be sensitive to data appearance…
Exploring Instance-Level Uncertainty for Medical Detection
Jiawei Yang, Yuan Liang, Yao Zhang +3
The ability of deep learning to predict with uncertainty is recognized as key for its adoption in clinical routines. Moreover, performance gain has been enabled by modelling uncert…
Accurate Anchor Free Tracking
Shengyun Peng, Yunxuan Yu, Kun Wang +1
Visual object tracking is an important application of computer vision. Recently, Siamese based trackers have achieved good accuracy. However, most of Siamese based trackers are not…