Listar por autor "Labayen, Mikel"

Mostrando ítems 1-3 de 3

Application of Computer Vision and Deep Learning in the railway domain for autonomous train stop operation

Arana-Arexolaleiba, Nestor (IEEE, 2020)

The purpose of this paper is to present the results of the analysis of the application of Deep Learning in the railway domain with a particular focus on a train stop operation. The paper proposes an approach consisting of ...
Monocular visual odometry for underground railway scenarios

Etxeberria Garcia, Mikel; Labayen, Mikel; Eizaguirre, Fernando; Zamalloa, Maider; Arana-Arexolaleiba, Nestor (SPIE, 2021)

In this paper, the application of monocular Visual Odometry (VO) solutions for underground train stopping operation are explored. In order to analyze if the application of monocular VO solutions in challenging environments as ...
Visual Odometry in Challenging Environments: An Urban Underground Railway Scenario Case

Arana-Arexolaleiba, Nestor (IEEE, 2022)

Localization is one of the most critical tasks for an autonomous vehicle, as position information is required to understand its surroundings and move accordingly. Visual Odometry (VO) has shown promising results in the ...