loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Adriana S. Iwashita ; Marcos V. T. Romero ; Alexandro Baldassin ; Kelton A. P. Costa and Joao P. Papa

Affiliation: São Paulo State University, Brazil

Keyword(s): Optimum-Path Forest, Graphics Processing Unit.

Abstract: In this paper, we presented a Graphics Processing Unit (GPU)-based training algorithm for Optimum-Path Forest (OPF) classifier. The proposed approach employs the idea of a vector-matrix multiplication to speed up both traditional OPF training algorithm and a recently proposed Central Processing Unit (CPU)-based OPF training algorithm. Experiments in several public datasets have showed the efficiency of the proposed approach, which demonstrated to be up to 14 times faster for some datasets. To the best of our knowledge, this is the first GPU-based implementation for OPF training algorithm.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.144.8.79

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
S. Iwashita, A.; V. T. Romero, M.; Baldassin, A.; A. P. Costa, K. and P. Papa, J. (2014). Training Optimum-Path Forest on Graphics Processing Units. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, pages 581-588. DOI: 10.5220/0004737805810588

@conference{visapp14,
author={Adriana {S. Iwashita}. and Marcos {V. T. Romero}. and Alexandro Baldassin. and Kelton {A. P. Costa}. and Joao {P. Papa}.},
title={Training Optimum-Path Forest on Graphics Processing Units},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={581-588},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004737805810588},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP
TI - Training Optimum-Path Forest on Graphics Processing Units
SN - 978-989-758-004-8
IS - 2184-4321
AU - S. Iwashita, A.
AU - V. T. Romero, M.
AU - Baldassin, A.
AU - A. P. Costa, K.
AU - P. Papa, J.
PY - 2014
SP - 581
EP - 588
DO - 10.5220/0004737805810588
PB - SciTePress