48 citations · 58 across the 5 of their papers we have counts for
5 papers
Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation
Qiangguo Jin, Hui Cui, Changming Sun +5
Acquiring pixel-level annotations is often limited in applications such as histology studies that require domain expertise. Various semi-supervised learning approaches have been de…
Graph-level Protein Representation Learning by Structure Knowledge Refinement
Ge Wang, Zelin Zang, Jiangbin Zheng +2
This paper focuses on learning representation on the whole graph level in an unsupervised manner. Learning graph-level representation plays an important role in a variety of real-w…
Co-modeling the Sequential and Graphical Routes for Peptide Representation Learning
Zihan Liu, Ge Wang, Jiaqi Wang +2
Peptides are formed by the dehydration condensation of multiple amino acids. The primary structure of a peptide can be represented either as an amino acid sequence or as a molecula…
CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment
Jiangbin Zheng, Yile Wang, Cheng Tan +5
Sign language recognition (SLR) is a weakly supervised task that annotates sign videos as textual glosses. Recent studies show that insufficient training caused by the lack of larg…
Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy
Yufei Huang, Lirong Wu, Haitao Lin +3
Learning meaningful protein representation is important for a variety of biological downstream tasks such as structure-based drug design. Having witnessed the success of protein se…