Distance measure with computer vision and neural networks for underwater applications

Luis M. Aristizabal; Carlos A. Zuluaga

doi:10.1109/CCRA.2016.7811421

Distance measure with computer vision and neural networks for underwater applications

Producción científica: Capítulo del libro/informe/acta de congreso › Ponencia publicada en las memorias del evento con ISBN › revisión exhaustiva

3 Citas (Scopus)

Resumen

This document describes a distance measurement system for underwater applications with computer vision and an Artificial Neural Network (ANN). The developed system is installed in the observation class remotely operated vehicle (ROV) Visor3, to be used in experimental testing. An integrated camera with two laser pointers are used to obtain input data to a Multi-Layer Perceptron (MLP) ANN, trained with a resilient backpropagation algorithm (RPROP). The solution described in this paper is an alternative to other methods found in the literature. Experimental results are presented.

Idioma original	Inglés
Título de la publicación alojada	2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings
Editores	Henry Carrillo Lindado
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781509037872
DOI	https://doi.org/10.1109/CCRA.2016.7811421
Estado	Publicada - 9 ene. 2017
Evento	1st IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Bogota D.C., Colombia Duración: 29 sep. 2016 → 30 sep. 2016

Serie de la publicación

Nombre	2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings

Conferencia

Conferencia	1st IEEE Colombian Conference on Robotics and Automation, CCRA 2016
País/Territorio	Colombia
Ciudad	Bogota D.C.
Período	29/09/16 → 30/09/16

Nota bibliográfica

Publisher Copyright:
© 2016 IEEE.

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10.1109/CCRA.2016.7811421

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Aristizabal, L. M., & Zuluaga, C. A. (2017). Distance measure with computer vision and neural networks for underwater applications. En H. C. Lindado (Ed.), 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings Artículo 7811421 (2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCRA.2016.7811421

Aristizabal, Luis M. ; Zuluaga, Carlos A. / Distance measure with computer vision and neural networks for underwater applications. 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings. editor / Henry Carrillo Lindado. Institute of Electrical and Electronics Engineers Inc., 2017. (2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings).

@inproceedings{904e70a7addc4b4d9d2018989f5c046e,

title = "Distance measure with computer vision and neural networks for underwater applications",

abstract = "This document describes a distance measurement system for underwater applications with computer vision and an Artificial Neural Network (ANN). The developed system is installed in the observation class remotely operated vehicle (ROV) Visor3, to be used in experimental testing. An integrated camera with two laser pointers are used to obtain input data to a Multi-Layer Perceptron (MLP) ANN, trained with a resilient backpropagation algorithm (RPROP). The solution described in this paper is an alternative to other methods found in the literature. Experimental results are presented.",

author = "Aristizabal, {Luis M.} and Zuluaga, {Carlos A.}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 1st IEEE Colombian Conference on Robotics and Automation, CCRA 2016 ; Conference date: 29-09-2016 Through 30-09-2016",

year = "2017",

month = jan,

day = "9",

doi = "10.1109/CCRA.2016.7811421",

language = "Ingl{\'e}s",

series = "2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings",

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Aristizabal, LM & Zuluaga, CA 2017, Distance measure with computer vision and neural networks for underwater applications. En HC Lindado (ed.), 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings., 7811421, 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 1st IEEE Colombian Conference on Robotics and Automation, CCRA 2016, Bogota D.C., Colombia, 29/09/16. https://doi.org/10.1109/CCRA.2016.7811421

Distance measure with computer vision and neural networks for underwater applications. / Aristizabal, Luis M.; Zuluaga, Carlos A.
2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings. ed. / Henry Carrillo Lindado. Institute of Electrical and Electronics Engineers Inc., 2017. 7811421 (2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Ponencia publicada en las memorias del evento con ISBN › revisión exhaustiva

TY - GEN

T1 - Distance measure with computer vision and neural networks for underwater applications

AU - Aristizabal, Luis M.

AU - Zuluaga, Carlos A.

PY - 2017/1/9

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N2 - This document describes a distance measurement system for underwater applications with computer vision and an Artificial Neural Network (ANN). The developed system is installed in the observation class remotely operated vehicle (ROV) Visor3, to be used in experimental testing. An integrated camera with two laser pointers are used to obtain input data to a Multi-Layer Perceptron (MLP) ANN, trained with a resilient backpropagation algorithm (RPROP). The solution described in this paper is an alternative to other methods found in the literature. Experimental results are presented.

AB - This document describes a distance measurement system for underwater applications with computer vision and an Artificial Neural Network (ANN). The developed system is installed in the observation class remotely operated vehicle (ROV) Visor3, to be used in experimental testing. An integrated camera with two laser pointers are used to obtain input data to a Multi-Layer Perceptron (MLP) ANN, trained with a resilient backpropagation algorithm (RPROP). The solution described in this paper is an alternative to other methods found in the literature. Experimental results are presented.

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DO - 10.1109/CCRA.2016.7811421

M3 - Ponencia publicada en las memorias del evento con ISBN

AN - SCOPUS:85012013367

T3 - 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings

BT - 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings

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PB - Institute of Electrical and Electronics Engineers Inc.

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Aristizabal LM , Zuluaga CA. Distance measure with computer vision and neural networks for underwater applications. En Lindado HC, editor, 2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. 7811421. (2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings). doi: 10.1109/CCRA.2016.7811421

Distance measure with computer vision and neural networks for underwater applications

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