원문정보
한국차세대컴퓨팅학회
한국차세대컴퓨팅학회 학술대회
The 7th International Conference on Next Generation Computing 2021
2021.11
pp.167-170
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Sewer pipes are an essential public infrastructure of countries worldwide. They support wastewater transportation for processing or disposal. The harsh environments inside the sewer pipes can lead to the occurrence of various defects. Current crack detection approaches mainly focus on the surveillance camera (CCTV) to assess the condition of the sewer pipes. This process is considered a tiresome and laborious process. Therefore, a robust and efficient sewer defect detection system based on the transformer architecture is introduced in this manuscript. In addition, the system can provide explainable visualization for its predictions using the transformer's attention.
목차
Abstract
I. INTRODUCTION
II. DATASET
A. CCTV Video Collection
B. Crack Detection Dataset Creation
III. METHODOLOGY
A. Pre-processing Module
B. Transformer-based Crack Detection Model
C. Attention Visualization
IV. EXPERIMENTAL RESULTS
A. Pre-processing Results
B. Transformer-based Crack Detection Performance
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
I. INTRODUCTION
II. DATASET
A. CCTV Video Collection
B. Crack Detection Dataset Creation
III. METHODOLOGY
A. Pre-processing Module
B. Transformer-based Crack Detection Model
C. Attention Visualization
IV. EXPERIMENTAL RESULTS
A. Pre-processing Results
B. Transformer-based Crack Detection Performance
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
저자정보
참고문헌
자료제공 : 네이버학술정보