271 citations · 1.3k across the 60 of their papers we have counts for
6 papers · 1 filter
Robust Deep Graph Based Learning for Binary Classification
Minxiang Ye, Vladimir Stankovic, Lina Stankovic +1
Convolutional neural network (CNN)-based feature learning has become state of the art, since given sufficient training data, CNN can significantly outperform traditional methods fo…
Graph Neural Net using Analytical Graph Filters and Topology Optimization for Image Denoising
Weng-tai Su, Gene Cheung, Richard Wildes +1
While convolutional neural nets (CNNs) have achieved remarkable performance for a wide range of inverse imaging applications, the filter coefficients are computed in a purely data-…
3D Point Cloud Super-Resolution via Graph Total Variation on Surface Normals
Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic
Point cloud is a collection of 3D coordinates that are discrete geometric samples of an object's 2D surfaces. Using a low-cost 3D scanner to acquire data means that point clouds ar…
Feature Graph Learning for 3D Point Cloud Denoising
Wei Hu, Xiang Gao, Gene Cheung +1
Identifying an appropriate underlying graph kernel that reflects pairwise similarities is critical in many recent graph spectral signal restoration schemes, including image denoisi…
Fast Graph Sampling Set Selection Using Gershgorin Disc Alignment
Yuanchao Bai, Fen Wang, Gene Cheung +2
Graph sampling set selection, where a subset of nodes are chosen to collect samples to reconstruct a smooth graph signal, is a fundamental problem in graph signal processing (GSP).…
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift
Fen Wang, Yongchao Wang, Gene Cheung +1
Matrix completion algorithms fill missing entries in a large matrix given a subset of observed samples. However, how to best pre-select informative matrix entries given a sampling…