activity
20202023
most citedLADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From Compressive Data

26 citations · 45 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SI2023

Nowcasting Temporal Trends Using Indirect Surveys

Ajitesh Srivastava, Juan Marcos Ramírez, Sergio Díaz-Aranda +4

Indirect surveys, in which respondents provide information about other people they know, have been proposed for estimating (nowcasting) the size of a \emph{hidden population} where…

eess.IV2021★ 26 cited

LADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From Compressive Data

Juan Marcos Ramírez, José Ignacio Martínez Torre, Henry Arguello Fuentes

Image fusion aims at estimating a high-resolution spectral image from a low-spatial-resolution hyperspectral image and a low-spectral-resolution multispectral image. In this regard…

eess.IV2021★ 3 cited

Subspace-Based Feature Fusion From Hyperspectral And Multispectral Image For Land Cover Classification

Juan Ramírez, Héctor Vargas, José Ignacio Martínez +1

In remote sensing, hyperspectral (HS) and multispectral (MS) image fusion have emerged as a synthesis tool to improve the data set resolution. However, conventional image fusion me…

eess.IV2021★ 8 cited

Covariance Estimation from Compressive Data Partitions using a Projected Gradient-based Algorithm

Jonathan Monsalve, Juan Ramirez, Iñaki Esnaola +1

Compressive covariance estimation has arisen as a class of techniques whose aim is to obtain second-order statistics of stochastic processes from compressive measurements. Recently…

eess.IV2020★ 8 cited

Feature Fusion via Dual-resolution Compressive Measurement Matrix Analysis For Spectral Image Classification

Juan Marcos Ramirez, Jose Ignacio Martinez-Torre, Henry Arguello

In the compressive spectral imaging (CSI) framework, different architectures have been proposed to recover high-resolution spectral images from compressive measurements. Since CSI…