Name
Title | ||
|---|---|---|
Deep Low-Dimensional Spectral Image Representation for Compressive Spectral Reconstruction |
Abstract | ||
|---|---|---|
Model-based deep learning techniques are the state-of-the-art in compressive spectral imaging reconstruction. These methods integrate deep neural networks (DNN) as spectral image representation used as prior information in the optimization problem, showing optimal results at the expense of increasing the dimensionality of the non-linear representation, i.e., the number of parameters to be recovere... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MLSP52302.2021.9596541 | 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP) |
Keywords | DocType | ISSN |
Deep learning,Training,Image coding,TV,Costs,Inverse problems,Imaging | Conference | 2161-0363 |
ISBN | Citations | PageRank |
978-1-7281-6338-3 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brayan Monroy | 1 | 0 | 0.34 |
| Jorge Bacca | 2 | 6 | 5.25 |
| Henry Arguello | 3 | 90 | 30.83 |