10 citations · 10 across the 2 of their papers we have counts for
6 papers · 1 filter
SDPT: Synchronous Dual Prompt Tuning for Fusion-based Visual-Language Pre-trained Models
Yang Zhou, Yongjian Wu, Jiya Saiyin +4
Prompt tuning methods have achieved remarkable success in parameter-efficient fine-tuning on large pre-trained models. However, their application to dual-modal fusion-based visual-…
RCdpia: A Renal Carcinoma Digital Pathology Image Annotation dataset based on pathologists
Qingrong Sun, Weixiang Zhong, Jie Zhou +3
The annotation of digital pathological slide data for renal cell carcinoma is of paramount importance for correct diagnosis of artificial intelligence models due to the heterogeneo…
Nucleus-aware Self-supervised Pretraining Using Unpaired Image-to-image Translation for Histopathology Images
Zhiyun Song, Penghui Du, Junpeng Yan +5
Self-supervised pretraining attempts to enhance model performance by obtaining effective features from unlabeled data, and has demonstrated its effectiveness in the field of histop…
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation
Yang Zhou, Yongjian Wu, Zihua Wang +5
Nuclei instance segmentation on histopathology images is of great clinical value for disease analysis. Generally, fully-supervised algorithms for this task require pixel-wise manua…
Gland Instance Segmentation by Deep Multichannel Neural Networks
Yan Xu, Yang Li, Mingyuan Liu +4
In this paper, we propose a new image instance segmentation method that segments individual glands (instances) in colon histology images. This is a task called instance segmentatio…
Gland Instance Segmentation by Deep Multichannel Side Supervision
Yan Xu, Yang Li, Mingyuan Liu +3
In this paper, we propose a new image instance segmentation method that segments individual glands (instances) in colon histology images. This is a task called instance segmentatio…