2 citations · 3 across the 5 of their papers we have counts for
5 papers
Using the Split Bregman Algorithm to Solve the Self-repelling Snake Model
Huizhu Pan, Jintao Song, Wanquan Liu +4
Preserving contour topology during image segmentation is useful in many practical scenarios. By keeping the contours isomorphic, it is possible to prevent over-segmentation and und…
Regularizing Semi-supervised Graph Convolutional Networks with a Manifold Smoothness Loss
Qilin Li, Wanquan Liu, Ling Li
Existing graph convolutional networks focus on the neighborhood aggregation scheme. When applied to semi-supervised learning, they often suffer from the overfitting problem as the…
A Novel Euler's Elastica based Segmentation Approach for Noisy Images via using the Progressive Hedging Algorithm
Lu Tan, Ling Li, Wanquan Liu +2
Euler's Elastica based unsupervised segmentation models have strong capability of completing the missing boundaries for existing objects in a clean image, but they are not working…
Semi-supervised Learning on Graph with an Alternating Diffusion Process
Qilin Li, Senjian An, Ling Li +1
Graph-based semi-supervised learning usually involves two separate stages, constructing an affinity graph and then propagating labels for transductive inference on the graph. It is…
Sparse Subspace Clustering via Diffusion Process
Qilin Li, Ling Li, Wanquan Liu
Subspace clustering refers to the problem of clustering high-dimensional data that lie in a union of low-dimensional subspaces. State-of-the-art subspace clustering methods are bas…