EFFICIENT LANE DETECTION BASED ON ARTIFICIAL NEURAL NETWORKS

F. Arce, E. Zamora, G. Hernández, H. Sossa

Resultado de la investigación: Contribución a una revistaArtículo de la conferenciarevisión exhaustiva

4 Citas (Scopus)

Resumen

Lane detection is a problem that has attracted in the last years the attention of the computer vision community. Most of approaches used until now to face this problem combine conventional image processing, image analysis and pattern classification techniques. In this paper, we propose a methodology based on so-called Ellipsoidal Neural Networks with Dendritic Processing (ENNDPs) as a new approach to provide a solution to this important problem. The functioning and performance of the proposed methodology is validated with a real video taken by a camera mounted on a car circulating on urban highway of Mexico City.

Idioma originalInglés
Páginas (desde-hasta)13-19
Número de páginas7
PublicaciónISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volumen4
N.º4W3
DOI
EstadoPublicada - 25 sep 2017
Evento2nd International Conference on Smart Data and Smart Cities, UDMS 2017 - Puebla, México
Duración: 4 oct 20176 oct 2017

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