Earticle

초록

영어

Recently, as e-scooter rental services are growing, e-scooter is considered as one of the most convenient and inexpensive means of transportation. As the use of e-scooters has soared in recent years, traffic accidents between vehicles and e-scooters riders have also increased. Therefore, there is also a need for the development of deep learning techniques for detecting e-scooters and riders. However, there is no large dataset labeled for e-scooters on the road captured by dash cameras on vehicles. In this paper, a new e-scooter dataset has been constructed using vehicles’ dashcam views to address this problem. This dataset consists of running e-scooters, parked e-scooters, e-scooter riders, and pedestrians. This paper also presents a CNN model for detecting e-scooters and riders, and analyzes the detection performance using our e-scooter dataset.

목차

Abstract
I. INTRODUCTION
II. CONSTRUCTING DATASET
III. TRAINING AND EVALUATION
IV. CONCLUSION
REFERENCES

저자

• Ji-Hyeon Ryu [ College of Electrical and Computer Engineering Chungbuk National University ]
• Hyung-Won Kim [ College of Electrical and Computer Engineering Chungbuk National University ] Corresponding Author

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