원문정보
한국차세대컴퓨팅학회
한국차세대컴퓨팅학회 학술대회
The 8th International Conference on Next Generation Computing 2022
2022.10
pp.86-87
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보