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20192023
most citedClass-Specific Distribution Alignment for Semi-Supervised Medical Image Classification

12 citations · 38 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023★ 12 cited

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…

cs.CV2023★ 8 cited

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…

cs.CV2023★ 1 cited

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…

cs.CV2023

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…

cs.CV2019

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…

cs.CV2019

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…