TY - JOUR
T1 - Practical Improvement and Performance Evaluation of Road Damage Detection Model using Machine Learning
AU - Fujii, Tomoya
AU - Jinki, Rie
AU - Horita, Yuukou
N1 - Publisher Copyright:
Copyright © 2023 The Institute of Electronics, Information and Communication Engineers.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - SUMMARY The social infrastructure, including roads and bridges built during period of rapid economic growth in Japan, is now aging, and there is a need to strategically maintain and renew the social infrastructure that is aging. On the other hand, road maintenance in rural areas is facing serious problems such as reduced budgets for maintenance and a shortage of engineers due to the declining birthrate and aging population. Therefore, it is difficult to visually inspect all roads in rural areas by maintenance engineers, and a system to automatically detect road damage is required. This paper reports practical improvements to the road damage model using YOLOv5, an object detection model capable of real-time operation, focusing on road image features.
AB - SUMMARY The social infrastructure, including roads and bridges built during period of rapid economic growth in Japan, is now aging, and there is a need to strategically maintain and renew the social infrastructure that is aging. On the other hand, road maintenance in rural areas is facing serious problems such as reduced budgets for maintenance and a shortage of engineers due to the declining birthrate and aging population. Therefore, it is difficult to visually inspect all roads in rural areas by maintenance engineers, and a system to automatically detect road damage is required. This paper reports practical improvements to the road damage model using YOLOv5, an object detection model capable of real-time operation, focusing on road image features.
KW - machine learning
KW - road damage detection
KW - road maintenance
UR - http://www.scopus.com/inward/record.url?scp=85170547626&partnerID=8YFLogxK
U2 - 10.1587/transfun.2022IML0003
DO - 10.1587/transfun.2022IML0003
M3 - 学術論文
AN - SCOPUS:85170547626
SN - 0916-8508
VL - E106.A
SP - 1216
EP - 1219
JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
IS - 9
ER -