@article{oai:kanazawa-u.repo.nii.ac.jp:00055253,
 author = {Machiguchi, Atsushi and Kita, Toshiharu and Tada, Norio and Takei, Hiromasa and Chikata, Yasuo and 町口, 敦志 and 喜多, 敏春 and 多田, 徳夫 and 武井, 宏将 and 近田, 康夫},
 journal = {構造工学論文集 A, Journal of structural engineering. A},
 month = {Mar},
 note = {In recent years, the problem of aging of infrastructure and countermeasures against lack of resources and technical shortage due to the declining birthrate and aging population are becoming a social issue. In maintaining and managing structures, it takes a great deal of labor and cost because there are huge numbers of stocks and high quality technicians are required to judge the deterioration factor at the time of inspection. This is a base study that aims to develop a system which mechanically judges the deterioration factor from photographs of deteriorated concrete structure with Deep learning which has produced many results in the field of image recognition and image authentication in recent years., 金沢大学理工研究域地球社会基盤学系},
 pages = {130--136},
 title = {ディープラーニングによるコンクリート構造物の劣化要因判定支援システムの開発に関する基礎的研究},
 volume = {64A},
 year = {2018}
}