Temporary Traffic Control Device Detection for Road Construction Projects Using Deep Learning Application

Author:

Seo Sungchul12345,Chen Donghui12345,Kim Kwangcheol12345,Kang Kyubyung12345,Koo Dan12345,Chae Myungjin12345,Park Hyung Keun12345

Affiliation:

1. Graduate Research Assistant, Dept. of Civil Engineering, Chungbuk National Univ., Cheongju, South Korea.

2. Graduate Research Assistant, Dept. of Computer and Information Science, Indiana Univ.–Purdue Univ. Indianapolis, Indianapolis, IN.

3. Undergraduate Research Assistant, Dept. of Mechanical Engineering, Indiana Univ.–Purdue Univ. Indianapolis, Indianapolis, IN.

4. Assistant Professor, School of Construction Management Technology, Purdue Univ., West Lafayette, IN. ORCID: https://orcid.org/0000-0572-0152-9081.

5. Associate Professor, Dept. of Engineering Technology, Indiana Univ.–Purdue Univ. Indianapolis, Indianapolis, IN.

Publisher

American Society of Civil Engineers

Reference13 articles.

1. Evaluation of deep neural networks for traffic sign detection systems;Arcos-Garcia A.;Neurocomputing,2018

2. Comparing machine learning and rule-based inferencing for semantic enrichment of BIM models

3. Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms

4. Chae, M., Kang, K., Koo, D., Oh, S., and Chun, J. Y. (2020). “Fuzzy Controller Algorithm for Automated HVAC Control.” In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 37, pp. 566–570). IAARC Publications.

5. Development of an Automated Visibility Analysis Framework for Pavement Markings Based on the Deep Learning Approach;Kang K.;Remote Sensing,2020

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