IEEE

A Subspace-Based Change Detection Method for Hyperspectral Images

Abstract: Remote sensing change detection has played an important role in many applications. Most traditional change detection methods deal with single-band or multispectral remote sensing images.
IEEE

Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery

Abstract: Principal component analysis (PCA) is one of the most widely used dimension reduction techniques. A related easier problem is termed subspace learning or subspace estimation. Given ...
GitHub

Official Tensorflow Code for the paper "Overcomplete Deep Subspace Clustering Networks" - WACV 2021

Deep Subspace Clustering Networks (DSC) provide an efficient solution to the problem of unsupervised subspace clustering by using an undercomplete deep auto-encoder with a fully-connected layer to ...
GitHub

Subspace Representation Learning for Sparse Linear Arrays to Localize More Sources than Sensors: A Deep Learning Methodology

This repository is the official implementation of the paper accepted by IEEE Transactions on Signal Processing, Subspace Representation Learning for Sparse Linear Arrays to Localize More Sources than ...