175 citations · 227 across the 7 of their papers we have counts for
8 papers
Signal Classification under structure sparsity constraints
Tiep Huu Vu
Object Classification is a key direction of research in signal and image processing, computer vision and artificial intelligence. The goal is to come up with algorithms that automa…
Classifying Multi-channel UWB SAR Imagery via Tensor Sparsity Learning Techniques
Tiep Vu, Lam Nguyen, Vishal Monga
Using low-frequency (UHF to L-band) ultra-wideband (UWB) synthetic aperture radar (SAR) technology for detecting buried and obscured targets, e.g. bomb or mine, has been successful…
Deep Network for Simultaneous Decomposition and Classification in UWB-SAR Imagery
Tiep Vu, Lam Nguyen, Tiantong Guo +1
Classifying buried and obscured targets of interest from other natural and manmade clutter objects in the scene is an important problem for the U.S. Army. Targets of interest are o…
Fast Low-rank Shared Dictionary Learning for Image Classification
Tiep Vu, Vishal Monga
Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. This observation has been exploited partially in a recent…
Adaptive matching pursuit for sparse signal recovery
Tiep H. Vu, Hojjat S. Mousavi, Vishal Monga
Spike and Slab priors have been of much recent interest in signal processing as a means of inducing sparsity in Bayesian inference. Applications domains that benefit from the use o…
Learning a low-rank shared dictionary for object classification
Tiep H. Vu, Vishal Monga
Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. Inspired by this observation, we propose a novel method t…