@article{ART003130940},
author={Ra Yeong Kim and Hyun-Jong Cha and Ah Reum Kang},
title={A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={10},
pages={69-75}
TY - JOUR
AU - Ra Yeong Kim
AU - Hyun-Jong Cha
AU - Ah Reum Kang
TI - A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 10
PB - The Korean Society Of Computer And Information
SP - 69
EP - 75
SN - 1598-849X
AB - Noise caused by adverse weather conditions in data collected during autonomous driving can lead to object recognition errors, potentially resulting in critical accidents. While this risk is widely acknowledged, there is a lack of research that quantitatively and systematically analyzes it. Therefore, this study aims to examine and quantify the extent to which noise affects object detection in autonomous driving environments. To this end, we utilized the YOLO v5 model trained on unprocessed datasets. The test data were divided into noise ratios of 0% (Original), 20%, 40%, 60%, and 80%, and the detection results were evaluated by constructing a Confusion Matrix. Experimental results show that as the noise ratio increases, the True Positive (TP) rate decreases, and the F1-score also significantly drops across all noise levels, specifically from 0.69 to 0.47, 0.29, 0.18, and 0.14. These findings are expected to contribute to enhancing the stability of autonomous driving technology. Future research will focus on collecting real datasets that include naturally occurring noise and developing more effective noise removal techniques.
KW - YOLO;Deep Learning;Object Detection;Data Quality;Computer Vision;Noise
DO -
UR -
ER -
Ra Yeong Kim, Hyun-Jong Cha and Ah Reum Kang. (2024). A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments. Journal of The Korea Society of Computer and Information, 29(10), 69-75.
Ra Yeong Kim, Hyun-Jong Cha and Ah Reum Kang. 2024, "A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments", Journal of The Korea Society of Computer and Information, vol.29, no.10 pp.69-75.
Ra Yeong Kim, Hyun-Jong Cha, Ah Reum Kang "A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments" Journal of The Korea Society of Computer and Information 29.10 pp.69-75 (2024) : 69.
Ra Yeong Kim, Hyun-Jong Cha, Ah Reum Kang. A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments. 2024; 29(10), 69-75.
Ra Yeong Kim, Hyun-Jong Cha and Ah Reum Kang. "A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 69-75.
Ra Yeong Kim; Hyun-Jong Cha; Ah Reum Kang. A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments. Journal of The Korea Society of Computer and Information, 29(10), 69-75.
Ra Yeong Kim; Hyun-Jong Cha; Ah Reum Kang. A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments. Journal of The Korea Society of Computer and Information. 2024; 29(10) 69-75.
Ra Yeong Kim, Hyun-Jong Cha, Ah Reum Kang. A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments. 2024; 29(10), 69-75.
Ra Yeong Kim, Hyun-Jong Cha and Ah Reum Kang. "A Study on the Impact of Noise on YOLO-based Object Detection in Autonomous Driving Environments" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 69-75.
