Traffic sign extraction using deep hierarchical feature learning and mobile light detection and ranging (LiDAR) data on rural highways-Reference-Cited by-同舟云学术

Traffic sign extraction using deep hierarchical feature learning and mobile light detection and ranging (LiDAR) data on rural highways

Published:2022-05-29 Issue: Volume: Page:1-22
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Gouda Maged¹^ORCID,Epp Alexander²,Tilroe Rowan²,El-Basyouny Karim¹

Affiliation:

1. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, Canada

2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Cette recherche a été financée par le Conseil de recherches en sciences naturelles et en génie du Canada

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2022.2074792

Reference61 articles.

1. Automatic road sign detecion and classification based on support vector machines and HOG descriptos

2. Automated Assessment of Passing Sight Distance on Rural Highways using Mobile LiDAR Data

3. Ai, C. & Tsai, Y. (2012). Critical assessment of automatic traffic sign detection using 3d LiDAR point cloud data. Transportation Research Part B.

4. Critical Assessment of an Enhanced Traffic Sign Detection Method Using Mobile LiDAR and INS Technologies

5. ArcMap. (2019). What is Lidar Intensity Data? ArcMap. Retrieved 2022, May 12, from http://desktop.arcgis.com/en/arcmap/103/manage-data/las-dataset/what-is-intensity-data-htm

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