Fast Optimum-Path Forest Classification on Graphics Processors

Marcos V. T. Romero, Adriana S. Iwashita, Luciene P. Papa, André N. Souza, João P. Papa

2014

Abstract

Some pattern recognition techniques may present a high computational cost for learning samples’ behaviour. The Optimum-Path Forest (OPF) classifier has been recently developed in order to overcome such drawbacks. Although it can achieve faster training steps when compared to some state-of-art techniques, OPF can be slower for testing in some situations. Therefore, we propose in this paper an implementation in graphics cards of the OPF classification, which showed to be more efficient than traditional OPF with similar accuracies.

Paper Citation

in Harvard Style

V. T. Romero M., S. Iwashita A., P. Papa L., N. Souza A. and P. Papa J. (2014). Fast Optimum-Path Forest Classification on Graphics Processors . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 627-631. DOI: 10.5220/0004740406270631

in Bibtex Style

@conference{visapp14,
author={Marcos V. T. Romero and Adriana S. Iwashita and Luciene P. Papa and André N. Souza and João P. Papa},
title={Fast Optimum-Path Forest Classification on Graphics Processors},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={627-631},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004740406270631},
isbn={978-989-758-004-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - Fast Optimum-Path Forest Classification on Graphics Processors
SN - 978-989-758-004-8
AU - V. T. Romero M.
AU - S. Iwashita A.
AU - P. Papa L.
AU - N. Souza A.
AU - P. Papa J.
PY - 2014
SP - 627
EP - 631
DO - 10.5220/0004740406270631