12 citations · 38 across the 9 of their papers we have counts for
9 papers
Class-Specific Distribution Alignment for Semi-Supervised Medical Image Classification
Zhongzheng Huang, Jiawei Wu, Tao Wang +2
Despite the success of deep neural networks in medical image classification, the problem remains challenging as data annotation is time-consuming, and the class distribution is imb…
Semi-Supervised Medical Image Segmentation with Co-Distribution Alignment
Tao Wang, Zhongzheng Huang, Jiawei Wu +2
Medical image segmentation has made significant progress when a large amount of labeled data are available. However, annotating medical image segmentation datasets is expensive due…
dugMatting: Decomposed-Uncertainty-Guided Matting
Jiawei Wu, Changqing Zhang, Zuoyong Li +3
Cutting out an object and estimating its opacity mask, known as image matting, is a key task in image and video editing. Due to the highly ill-posed issue, additional inputs, typic…
Spatio-Temporal Context Modeling for Road Obstacle Detection
Xiuen Wu, Tao Wang, Lingyu Liang +2
Road obstacle detection is an important problem for vehicle driving safety. In this paper, we aim to obtain robust road obstacle detection based on spatio-temporal context modeling…
Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks
Fengbin Zhang, Haoyi Fan, Ruidong Wang +2
Networks are ubiquitous in the real world such as social networks and communication networks, and anomaly detection on networks aims at finding nodes whose structural or attributed…
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks
Haoyi Fan, Fengbin Zhang, Zuoyong Li
Anomaly detection on attributed networks aims at finding nodes whose patterns deviate significantly from the majority of reference nodes, which is pervasive in many applications su…
Correlation-aware Deep Generative Model for Unsupervised Anomaly Detection
Haoyi Fan, Fengbin Zhang, Ruidong Wang +2
Unsupervised anomaly detection aims to identify anomalous samples from highly complex and unstructured data, which is pervasive in both fundamental research and industrial applicat…
Robust Classification with Sparse Representation Fusion on Diverse Data Subsets
Chun-Mei Feng, Yong Xu, Zuoyong Li +1
Sparse Representation (SR) techniques encode the test samples into a sparse linear combination of all training samples and then classify the test samples into the class with the mi…
Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering
Songsong Wu, Zhiqiang Lu, Hao Tang +4
Multi-view subspace clustering aims to divide a set of multisource data into several groups according to their underlying subspace structure. Although the spectral clustering based…