Autores
Arce Vega Fernando
Sossa Azuela Juan Humberto
Hernández Hernández Gerardo
Título Efficient Lane Detection based on Artificial Neural Networks
Tipo Congreso
Sub-tipo Memoria
Descripción 2nd International Conference on Smart Data and Smart Cities, UDMS 2017
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.
Observaciones doi: 10.5194/isprs-annals-IV-4-W3-13-2017
Lugar Puebla
País Mexico
No. de páginas 13-19
Vol. / Cap.
Inicio 2017-10-04
Fin 2017-10-06
ISBN/ISSN