540 citations
- Chinese Academy of SciencesCN14 papers
- Institute of Computing TechnologyCN12 papers
- University of Chinese Academy of SciencesCN9 papers
- Tsinghua UniversityCN6 papers
- Shanghai Jiao Tong UniversityCN5 papers
- City University of Hong KongHK3 papers
- Fudan UniversityCN3 papers
- Hefei University of TechnologyCN3 papers
- South China University of TechnologyCN3 papers
- University of California, Los AngelesUS3 papers
- Zhejiang UniversityCN3 papers
- Beijing Jiaotong UniversityCN2 papers
7 papers · 1 filter
HoloBoard: a Large-format Immersive Teaching Board based on pseudo HoloGraphics
Jiangtao Gong, Teng Han, Siling Guo +6
In this paper, we present HoloBoard, an interactive large-format pseudo-holographic display system for lecture-based classes. With its unique properties of immersive visual display…
Pooling Architecture Search for Graph Classification
Lanning Wei, Huan Zhao, Quanming Yao +1
Graph classification is an important problem with applications across many domains, like chemistry and bioinformatics, for which graph neural networks (GNNs) have been state-of-the…
LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching
Kun Zhang, Guangyi Lv, Le Wu +3
Sentence semantic matching requires an agent to determine the semantic relation between two sentences, which is widely used in various natural language tasks, such as Natural Langu…
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…
Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
Yao Zhang, Jiawei Yang, Jiang Tian +4
Liver cancer is one of the most common cancers worldwide. Due to inconspicuous texture changes of liver tumor, contrast-enhanced computed tomography (CT) imaging is effective for t…
ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
Yixin Wang, Yang Zhang, Yang Liu +6
Accurate segmentation of brain tumors from magnetic resonance imaging (MRI) is clinically relevant in diagnoses, prognoses and surgery treatment, which requires multiple modalities…