Publications (9)
Core-periphery Detection Based on Masked Bayesian Non-negative Matrix Factorization
Zhonghao Wang, Ru Yuan, Jiaye Fu +2
Core-periphery structure is an essential mesoscale feature in complex networks. Previous researches mostly focus on discriminative approaches while in this work, we propose a gener…
A Multi-View Consistency Framework with Semi-Supervised Domain Adaptation
Yuting Hong, Li Dong, Xiaojie Qiu +4
Semi-Supervised Domain Adaptation (SSDA) leverages knowledge from a fully labeled source domain to classify data in a partially labeled target domain. Due to the limited number of…
Semi-Supervised Semantic Segmentation with Cross Teacher Training
Hui Xiao, Li Dong, Kangkang Song +4
Convolutional neural networks can achieve remarkable performance in semantic segmentation tasks. However, such neural network approaches heavily rely on costly pixel-level annotati…
Exploiting Minority Pseudo-Labels for Semi-Supervised Fine-grained Road Scene Understanding
Yuting Hong, Yongkang Wu, Hui Xiao +4
In fine-grained road scene understanding, semantic segmentation plays a crucial role in enabling vehicles to perceive and comprehend their surroundings. By assigning a specific cla…
Semi-Supervised Learning with Pseudo-Negative Labels for Image Classification
Hao Xu, Hui Xiao, Huazheng Hao +3
Semi-supervised learning frameworks usually adopt mutual learning approaches with multiple submodels to learn from different perspectives. To avoid transferring erroneous pseudo la…
Image restoration quality assessment based on regional differential information entropy
Zhiyu Wang, Jiayan Zhuang, Ningyuan Xu +3
With the development of image recovery models,especially those based on adversarial and perceptual losses,the detailed texture portions of images are being recovered more naturally…
Directed Link Prediction using GNN with Local and Global Feature Fusion
Yuyang Zhang, Xu Shen, Yu Xie +3
Link prediction is a classical problem in graph analysis with many practical applications. For directed graphs, recently developed deep learning approaches typically analyze node s…
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-supervised Semantic Segmentation
Hui Xiao, Yuting Hong, Li Dong +5
Semi-supervised semantic segmentation relieves the reliance on large-scale labeled data by leveraging unlabeled data. Recent semi-supervised semantic segmentation approaches mainly…
Accelerating Community Detection by Using K-core Subgraphs
Chengbin Peng, Tamara G. Kolda, Ali Pinar
Community detection is expensive, and the cost generally depends at least linearly on the number of vertices in the graph. We propose working with a reduced graph that has many few…