52 citations · 124 across the 15 of their papers we have counts for
5 papers · 1 filter
Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition
Jin Ye, Junjun He, Xiaojiang Peng +2
Recent studies often exploit Graph Convolutional Network (GCN) to model label dependencies to improve recognition accuracy for multi-label image recognition. However, constructing…
MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response
Jiancheng Yang, Jiajun Chen, Kaiming Kuang +3
Predicting clinical outcome is remarkably important but challenging. Research efforts have been paid on seeking significant biomarkers associated with the therapy response or/and p…
EfficientFCN: Holistically-guided Decoding for Semantic Segmentation
Jianbo Liu, Junjun He, Jiawei Zhang +2
Both performance and efficiency are important to semantic segmentation. State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (…
Tensor Low-Rank Reconstruction for Semantic Segmentation
Wanli Chen, Xinge Zhu, Ruoqi Sun +4
Context information plays an indispensable role in the success of semantic segmentation. Recently, non-local self-attention based methods are proved to be effective for context inf…
Learning to Predict Context-adaptive Convolution for Semantic Segmentation
Jianbo Liu, Junjun He, Jimmy S. Ren +2
Long-range contextual information is essential for achieving high-performance semantic segmentation. Previous feature re-weighting methods demonstrate that using global context for…