Tracking for a CNN guided robot

Giovanni Egidio Pazienza; Pasqualino Giangrossi; Sebastià Tortella; Marco Balsi; Xavier Vilasís-Cardona

doi:10.1109/ECCTD.2005.1523064

Tracking for a CNN guided robot

Giovanni Egidio Pazienza^*
, Pasqualino Giangrossi
, Sebastià Tortella
, Marco Balsi
, Xavier Vilasís-Cardona

^*Autor/a de correspondencia de este trabajo

Producción científica: Capítulo del libro › Contribución a congreso/conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

Cellular Neural Networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper we present an algorithm for tracking using CNNs. We successfully tested the algorithm on an autonomous robot guided using only real-time visual feedback; the image processing is performed entirely by a CNN system embedded in a DSP.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2005 European Conference on Circuit Theory and Design
Páginas	77-80
Número de páginas	4
DOI	https://doi.org/10.1109/ECCTD.2005.1523064
Estado	Publicada - 2005
Publicado de forma externa	Sí
Evento	2005 European Conference on Circuit Theory and Design - Cork, Irlanda Duración: 28 ago 2005 → 2 sept 2005

Serie de la publicación

Nombre	Proceedings of the 2005 European Conference on Circuit Theory and Design
Volumen	3

Conferencia

Conferencia	2005 European Conference on Circuit Theory and Design
País/Territorio	Irlanda
Ciudad	Cork
Período	28/08/05 → 2/09/05

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10.1109/ECCTD.2005.1523064

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@inproceedings{393d04ad262c44649a82139895adbd61,

title = "Tracking for a CNN guided robot",

abstract = "Cellular Neural Networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper we present an algorithm for tracking using CNNs. We successfully tested the algorithm on an autonomous robot guided using only real-time visual feedback; the image processing is performed entirely by a CNN system embedded in a DSP.",

author = "Pazienza, \{Giovanni Egidio\} and Pasqualino Giangrossi and Sebasti{\`a} Tortella and Marco Balsi and Xavier Vilas{\'i}s-Cardona",

year = "2005",

doi = "10.1109/ECCTD.2005.1523064",

language = "English",

isbn = "0780390660",

series = "Proceedings of the 2005 European Conference on Circuit Theory and Design",

pages = "77--80",

booktitle = "Proceedings of the 2005 European Conference on Circuit Theory and Design",

note = "2005 European Conference on Circuit Theory and Design ; Conference date: 28-08-2005 Through 02-09-2005",

}

Pazienza, GE, Giangrossi, P, Tortella, S, Balsi, M & Vilasís-Cardona, X 2005, Tracking for a CNN guided robot. En Proceedings of the 2005 European Conference on Circuit Theory and Design., 1523064, Proceedings of the 2005 European Conference on Circuit Theory and Design, vol. 3, pp. 77-80, 2005 European Conference on Circuit Theory and Design, Cork, Irlanda, 28/08/05. https://doi.org/10.1109/ECCTD.2005.1523064

Tracking for a CNN guided robot. / Pazienza, Giovanni Egidio; Giangrossi, Pasqualino; Tortella, Sebastià et al.
Proceedings of the 2005 European Conference on Circuit Theory and Design. 2005. p. 77-80 1523064 (Proceedings of the 2005 European Conference on Circuit Theory and Design; Vol. 3).

Producción científica: Capítulo del libro › Contribución a congreso/conferencia › revisión exhaustiva

TY - GEN

T1 - Tracking for a CNN guided robot

AU - Pazienza, Giovanni Egidio

AU - Giangrossi, Pasqualino

AU - Tortella, Sebastià

AU - Balsi, Marco

AU - Vilasís-Cardona, Xavier

PY - 2005

Y1 - 2005

N2 - Cellular Neural Networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper we present an algorithm for tracking using CNNs. We successfully tested the algorithm on an autonomous robot guided using only real-time visual feedback; the image processing is performed entirely by a CNN system embedded in a DSP.

AB - Cellular Neural Networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper we present an algorithm for tracking using CNNs. We successfully tested the algorithm on an autonomous robot guided using only real-time visual feedback; the image processing is performed entirely by a CNN system embedded in a DSP.

UR - https://www.scopus.com/pages/publications/33749028474

U2 - 10.1109/ECCTD.2005.1523064

DO - 10.1109/ECCTD.2005.1523064

M3 - Conference contribution

AN - SCOPUS:33749028474

SN - 0780390660

SN - 9780780390669

T3 - Proceedings of the 2005 European Conference on Circuit Theory and Design

SP - 77

EP - 80

BT - Proceedings of the 2005 European Conference on Circuit Theory and Design

T2 - 2005 European Conference on Circuit Theory and Design

Y2 - 28 August 2005 through 2 September 2005

ER -

Tracking for a CNN guided robot

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