Search Results for author:
Found 11 papers, 3 papers with code
RFVTM: A Recovery and Filtering Vertex Trichotomy Matching for Remote Sensing Image Registration
In this paper, a robust feature point matching algorithm called Recovery and Filtering Vertex Trichotomy Matching (RFVTM) is proposed to remove outliers and retain sufficient inliers for remote sensing images.
A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation
This paper proposes a new deep-unfolding-based network design for the problem of Robust Principal Component Analysis (RPCA) with application to video foreground-background separation.
Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted $\ell_1$-$\ell_1$ Minimization: Architecture Design and Generalization Analysis
In this line of research, this paper develops a novel deep recurrent neural network (coined reweighted-RNN) by the unfolding of a reweighted $\ell_1$-$\ell_1$ minimization algorithm and applies it to the task of sequential signal reconstruction.
A Deep Recurrent Neural Network via Unfolding Reweighted l1-l1 Minimization
In this line of research, this paper develops a novel deep recurrent neural network (coined reweighted-RNN) by unfolding a reweighted l1-l1 minimization algorithm and applies it to the task of sequential signal reconstruction.
Designing recurrent neural networks by unfolding an l1-l1 minimization algorithm
We propose a new deep recurrent neural network (RNN) architecture for sequential signal reconstruction.
Online Decomposition of Compressive Streaming Data Using $n$-$\ell_1$ Cluster-Weighted Minimization
The proposed decomposition solves an $n$-$\ell_1$ cluster-weighted minimization to decompose a sequence of frames (or vectors), into sparse and low-rank components, from compressive measurements.
Compressive Online Robust Principal Component Analysis with Optical Flow for Video Foreground-Background Separation
The proposed method is applied to online video foreground and background separation from compressive measurements.
Incorporating Prior Information in Compressive Online Robust Principal Component Analysis
In addition, we apply the proposed algorithm to online video foreground and background separation from compressive measurements.
Distributed Coding of Multiview Sparse Sources with Joint Recovery
In support of applications involving multiview sources in distributed object recognition using lightweight cameras, we propose a new method for the distributed coding of sparse sources as visual descriptor histograms extracted from multiview images.
Sparse Signal Reconstruction with Multiple Side Information using Adaptive Weights for Multiview Sources
This two-level optimization leads the proposed reconstruction algorithm with multiple SI using adaptive weights (RAMSIA) to robustly exploit the multiple SIs with different qualities.
Measurement Bounds for Sparse Signal Reconstruction with Multiple Side Information
To address this problem, we theoretically study a generic \textcolor{black}{weighted $n$-$\ell_{1}$ minimization} framework and propose a reconstruction algorithm that leverages multiple side information signals (RAMSI).
