@article{oai:nagasaki-u.repo.nii.ac.jp:00000250,
 author = {寺野, 聡恭 and 古賀, 掲維 and 松田, 浩},
 issue = {93},
 journal = {長崎大学大学院工学研究科研究報告, Reports of Graduate School of Engineering, Nagasaki University},
 month = {Aug},
 note = {In a local government, proper maintenance and management of social infrastructure such as roads and bridges is a very important activity to live a life. However, in recent years, the aging of concrete structures constructed during the period of high economic growth has become a problem. Under such circumstances, the demand for maintenance of social infrastructure is expected to increase in the future, and it is necessary to develop more efficient methods. In the inspection of concrete structures, it is fundamental to observe the occurrence of cracks. In this study, we aimed to develop a diagnostic method for cracks and confirmed that it is effective for remarkable cracks in concrete structures by transfer learning, which is one method of deep learning from digital photographs., 長崎大学大学院工学研究科研究報告, 49(93), pp.119-124; 2019},
 pages = {119--124},
 title = {深層学習を用いたコンクリートのひび割れ検出プログラムに関する研究},
 volume = {49},
 year = {2019}
}