Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Alejandro Parada Mayorga"'
Publikováno v:
Ingeniería e Investigación, Vol 34, Iss 3, Pp 50-55 (2014)
The Coded Aperture Snapshot Spectral Imaging (CASSI) system captures the three-dimensional (3D) spatio-spectral information of a scene using a set of two-dimensional (2D) random-coded Focal Plane Array (FPA) measurements. A compressive sensing recons
Externí odkaz:
https://doaj.org/article/c19457596ada4d04bcc8da8aaf028e99
Publikováno v:
IEEE Transactions on Signal Processing. 69:3351-3366
We study algebraic neural networks (AlgNNs) with commutative algebras which unify diverse architectures such as Euclidean convolutional neural networks, graph neural networks, and group neural networks under the umbrella of algebraic signal processin
Publikováno v:
IEEE Signal Processing Magazine. 37:31-42
With the surge in the volumes and dimensions of data defined in non-Euclidean spaces, graph signal processing (GSP) techniques are emerging as important tools in our understanding of these domains [1]. A fundamental problem for GSP is to determine wh
Graph convolutional learning has led to many exciting discoveries in diverse areas. However, in some applications, traditional graphs are insufficient to capture the structure and intricacies of the data. In such scenarios, multigraphs arise naturall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::076612d6bb317540d56fda7dc6b0ffe4
Publikováno v:
ICASSP
Algebraic neural networks (AlgNNs) are composed of a cascade of layers each one associated to and algebraic signal model, and information is mapped between layers by means of a nonlinearity function. AlgNNs provide a generalization of neural network
Publikováno v:
EUSIPCO
Graph neural networks (GNNs) have been used effectively in different applications involving the processing of signals on irregular structures modeled by graphs. Relying on the use of shift-invariant graph filters, GNNs extend the operation of convolu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::326f2df56f7ddab05a278afa5645f29a
Publikováno v:
IEEE Transactions on Computational Imaging. 3:202-216
Colored coded aperture optimization in compressive spectral imaging is discussed. Based on the analysis of the coherence of the underlying sensing matrix, a general family of codes is derived. These designs lead to reconstructions of multispectral sc
Publikováno v:
2019 13th International conference on Sampling Theory and Applications (SampTA).
In this work we introduce the concept of blue noise sampling, traditionally used in imaging applications, for bandlimited signals on graphs. We show how the spectral and vertex domain characterization of these patterns is connected with results about
Publikováno v:
DSW
This paper discusses the generalization of the concept of blue noise sampling from traditional halftoning to signal processing on graphs. Making use of the spatial properties of blue noise, we generate sampling patterns that provide reconstruction er
Publikováno v:
DSW
In this paper, we calculate the optimal sampling sets for bandlimited signals on cographs. We take into account the tree structure of the cograph to derive closed form results for the uniqueness sets of signals with a given bandwidth. These results d