Earticle

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

저자

• Minh Dang [ Department of Computer Science and Engineering, Sejong University ]
• Kyungbok Min [ Department of Computer Science and Engineering, Sejong University ]
• Hyeonjoon Moon [ Department of Computer Science and Engineering, Sejong University ] Corresponding Author

참고문헌