Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and k -Nearest Neighbor Scheme

Obstacle detection is an essential element for the development of intelligent transportation systems so that accidents can be avoided. In this paper, we propose a stereovision-based method for detecting obstacles in urban environment. The proposed method uses a deep stacked auto-encoders (DSA) model...

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Bibliographic Details

Published in:	IEEE sensors journal Vol. 18; no. 12; pp. 5122 - 5132
Main Authors:	Dairi, Abdelkader, Harrou, Fouzi, Ying Sun, Senouci, Mohamed
Format:	Journal Article
Language:	English
Published:	IEEE 15.06.2018
Subjects:	autonomous vehicles Clustering algorithms deep learning intelligent transportation systems Kernel Machine learning Machine learning algorithms Obstacle detection Partitioning algorithms Roads Sensors
ISSN:	1530-437X, 1558-1748
Online Access:	Get full text
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