Transforms of Hough Type in Abstract Feature Space: Generalized Precedents

Elena Nelyubina, Vladimir Ryazanov, Alexander Vinogradov

2017

Abstract

In this paper the role of intrinsic and introduced data structures in constructing efficient data analysis algorithms is analyzed. We investigate the concept of generalized precedent and based on its use transforms of Hough type for search dependencies in data, reduction of dimension, and improvement of decision rule.

Paper Citation

in Harvard Style

Nelyubina E., Ryazanov V. and Vinogradov A. (2017). Transforms of Hough Type in Abstract Feature Space: Generalized Precedents . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 651-656. DOI: 10.5220/0006270806510656

in Bibtex Style

@conference{visapp17,
author={Elena Nelyubina and Vladimir Ryazanov and Alexander Vinogradov},
title={Transforms of Hough Type in Abstract Feature Space: Generalized Precedents},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={651-656},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006270806510656},
isbn={978-989-758-225-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Transforms of Hough Type in Abstract Feature Space: Generalized Precedents
SN - 978-989-758-225-7
AU - Nelyubina E.
AU - Ryazanov V.
AU - Vinogradov A.
PY - 2017
SP - 651
EP - 656
DO - 10.5220/0006270806510656