Evaluation of Multiclass Traffic Sign Detection and Classification Methods for U.S. Roadway Asset Inventory Management-Reference-Cited by-同舟云学术

Evaluation of Multiclass Traffic Sign Detection and Classification Methods for U.S. Roadway Asset Inventory Management

Published:2016-03 Issue:2 Volume:30 Page:04015022
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Balali Vahid¹,Golparvar-Fard Mani²

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801 (corresponding author).

2. Assistant Professor, Dept. of Civil and Environmental Engineering and Dept. of Computer Science, Univ. of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000491

Reference79 articles.

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3. Ali N. Sobran N. Ghazaly M. M. Shukor S. A. and Ibrahim A. F. T. (2014). “Traffic sign detection and classification for driver assistant system.” 8th Int. Conf. on Robotic Vision Signal Processing & Power Applications H. A. Mat Sakim and M. T. Mustaffa eds. Springer Singapore 277–283.

4. ASCE. (2013). “National infrastructure report card.” Reston VA.

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