A parallel generalized relaxation method for high-performance image segmentation on GPUs
type: Item
instance of: scholarly article
title: A parallel generalized relaxation method for high-performance image segmentation on GPUs
zbMATH Open document ID: 1322.65071
author: Pasqua D'Ambra
author: Salvatore Filippone
published in: Journal of Computational and Applied Mathematics
publication date: 2015-10-19T00:00:00Z
Mathematics Subject Classification ID: 65K10
Mathematics Subject Classification ID: 65N22
Mathematics Subject Classification ID: 65Y05
Mathematics Subject Classification ID: 68T45
Mathematics Subject Classification ID: 65-04
zbMATH DE Number: 6496046
zbMATH Keywords: image segmentation
zbMATH Keywords: variational models
zbMATH Keywords: relaxation methods
zbMATH Keywords: GPU
describes a project that uses: 2LEV-D2P4
describes a project that uses: ITPACK 2C
describes a project that uses: MLD2P4
describes a project that uses: Paralution
describes a project that uses: ITPACK
describes a project that uses: STREAM benchmark
describes a project that uses: CUSPARSE
describes a project that uses: CUDA
describes a project that uses: PSBLAS
MaRDI profile type: Publication
full work available at URL: j.cam.2015.04.035
OpenAlex ID: W2065973083
cites work: Mumford and Shah Model and its Applications to Image Segmentation andImage Restoration
cites work: PSBLAS
cites work: Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003
cites work: 2LEV-D2P4: a package of high-performance preconditioners for scientific and engineering applications
cites work: MLD2P4
cites work: Approximation of functional depending on jumps by elliptic functional via t-convergence
cites work: Q4792091
cites work: Parallel iterative methods for sparse linear systems
cites work: Sparse Matrix-Vector Multiplication on GPGPUs
DOI: 10.1016/J.CAM.2015.04.035
description: scientific article; zbMATH DE number 6496046