An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN

Emin Güney; Cüneyt Bayılmış

doi:10.35377/saucis...1073355

EN

An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN

Abstract

Traffic signs and road objects detection is significant issue for driver safety. It has become popular with the development of autonomous vehicles and driver-assistant systems. This study presents a real-time system that detects traffic signs and various objects in the driving environment with a camera. Faster R-CNN architecture was used as a detection method in this study. This architecture is a well-known two-stage approach for object detection. Dataset was created by collecting various images for training and testing of the model. The dataset consists of 1880 images containing traffic signs and objects collected from Turkey with the GTSRB dataset. These images were combined and divided into the training set and testing set with the ratio of 80/20. The model's training was carried out in the computer environment for 8.5 hours and approximately 10000 iterations. Experimental results show the real-time performance of Faster R-CNN for robustly traffic signs and objects detection.

Keywords

Supporting Institution

Sakarya University Scientific Research Projects Coordination Unit

Project Number

2021-7-24-20

Thanks

We want to thank our hardworking teammates Neslihan ÇAKIRBAŞ, Havva Selin ÇAKMAK, Ali Göktuğ YALÇIN and Dilara KOCA. They helped us prepare the datasets and the development of the system.

References

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Details

Primary Language

English

Subjects

Computer Software

Journal Section

Research Article

Authors

Emin Güney ^*
0000-0003-0098-9018
Türkiye

Cüneyt Bayılmış
0000-0003-1058-7100
Türkiye

Publication Date

August 31, 2022

Submission Date

February 14, 2022

Acceptance Date

July 22, 2022

Published in Issue

Year 2022 Volume: 5 Number: 2

DOI

https://doi.org/10.35377/saucis...1073355

IZ

https://izlik.org/JA29PZ24YF

Cite

RIS / Bibtex

APA

Güney, E., & Bayılmış, C. (2022). An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN. Sakarya University Journal of Computer and Information Sciences, 5(2), 216-224. https://doi.org/10.35377/saucis...1073355

AMA

1.Güney E, Bayılmış C. An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN. SAUCIS. 2022;5(2):216-224. doi:10.35377/saucis.1073355

Chicago

Güney, Emin, and Cüneyt Bayılmış. 2022. “An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN”. Sakarya University Journal of Computer and Information Sciences 5 (2): 216-24. https://doi.org/10.35377/saucis. 1073355.

EndNote

Güney E, Bayılmış C (August 1, 2022) An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN. Sakarya University Journal of Computer and Information Sciences 5 2 216–224.

IEEE

[1]E. Güney and C. Bayılmış, “An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN”, SAUCIS, vol. 5, no. 2, pp. 216–224, Aug. 2022, doi: 10.35377/saucis...1073355.

ISNAD

Güney, Emin - Bayılmış, Cüneyt. “An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN”. Sakarya University Journal of Computer and Information Sciences 5/2 (August 1, 2022): 216-224. https://doi.org/10.35377/saucis. 1073355.

JAMA

1.Güney E, Bayılmış C. An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN. SAUCIS. 2022;5:216–224.

MLA

Güney, Emin, and Cüneyt Bayılmış. “An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN”. Sakarya University Journal of Computer and Information Sciences, vol. 5, no. 2, Aug. 2022, pp. 216-24, doi:10.35377/saucis. 1073355.

Vancouver

1.Emin Güney, Cüneyt Bayılmış. An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN. SAUCIS. 2022 Aug. 1;5(2):216-24. doi:10.35377/saucis. 1073355

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IEEE Access

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Construction Robotics

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An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN

Öz

An Implementation of Traffic Signs and Road Objects Detection Using Faster R-CNN

Abstract

Keywords

Supporting Institution

Project Number

Thanks

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

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