Earticle

초록

영어

As the number of vehicle drivers is increasing day by day, the risk of traffic accidents is also increasing. Among the accidents, there are tire-related accidents causes huge damage if it occurs. These kinds of accidents could be prevented through safety checks of tire, but drivers usually overlook it because they don’t have the knowledge to know what the condition of the tire and don’t want to spend time and money to safety inspection and so on. To solve these problems, we propose tire life prediction mobile application with deep-learning method to check the condition of tires simply. Also, considering the embedded environment that has low power and capacity, we apply lightweight technique called pruning

목차

Abstract
I. INTRODUCTION
II. PROPOSED METHOD
A. Experiment with performance comparision between classification and regression methodology
B. Building a data pipeline for tire image and label
C. Data preprocessing using deep learning based tire segmentation method
D. Apply L1 based filter pruning
III. EXPERIMENT
IV. RESULT
REFERENCES

키워드

저자

• Ho Jun, Yang [ Department of Electrical & Computer Engineering Inha University ]
• Sang Bong, Yoo [ Department of Computer Engineering Inha University ]
• Jang Woo, Kwon [ Department of Computer Engineering Inha University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004