Earticle

초록

영어

With global concerns mounting over the aging of infrastructure and roadways, and the growing emphasis on road maintenance, safety inspections have become a critical priority. Current crack detection models face challenges related to feature loss and performance degradation. In response, we propose an Attention U-Net model designed to minimize information loss and improve crack detection performance, particularly in low-quality images. Additionally, we focus on optimizing image capture and detection on low-spec devices, leading to the development of a lightweight model that performs effectively even in resource-constrained environments.

목차

Abstract
I. INTRODUCTION
II. PROPOSED METHOD
A. Attention Mechanism
B. Network Architecture
C. Dataset
D. Loss Function
E. Training Environment
F. Comparision Method
III. RESULT
IV. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• Ju-Hyeon Noh [ Dept. of Computer Engineering Chosun University Gwangju 61452, Republic of Korea ]
• Joon-Hyeok Kim [ Dept. of Computer Engineering Chosun University Gwangju 61452, Republic of Korea ]
• Jun-Young Jang [ Dept. of Computer Engineering Chosun University Gwangju 61452, Republic of Korea ]
• Hee-Deok Yang [ Dept. of Computer Engineering Chosun University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004