Session Details
土木分野におけるAIの活用(その11)
Fri. Sep 4, 2026 3:10 PM - 4:30 PM JST
Fri. Sep 4, 2026 6:10 AM - 7:30 AM UTC
Fri. Sep 4, 2026 6:10 AM - 7:30 AM UTC
Room D60, 6th Floor, Building 7 (Hokkai-Gakuen University)
[CS14-76]A Basic Study on Detecting Separation Between Concrete Blocks in Fishing Port Structures Using Deep Learning
*Yasunari Miyashita1,4, Takayasu Fujita2, Masanori Takeda2, Nobuo Mikami3, Atsushi Mikami1 (1. Tokai University, 2. Fisheries Infrastructure Development Center, 3. North Japan Port Consultants Inc , 4. Japan Port Consultants Inc)
[CS14-77]A fundamental study on a rebar exposure and crack detection system using a 360-degree camera and YOLO
*Sota Sato1, Kohaku Kobayashi2, Koichi Komiyama1, Kou Ibayashi1 (1. National Institute of Technology, Nagaoka College, 2. Japan Advanced Institute of Science and Technology)
[CS14-78]Study on Estimating the Strength of Sulfuric Acid-Corroded Concrete from Surface Images Using Machine Learning
*Yuki Mimura1, Hisatoshi Kasahara1, Yoshihiro Iriyama1, Takashi Miwa1 (1. NTT, Inc)
[CS14-79]Development of an Integrated System for Infrastructure Damage Mapping Using Large-Scale Image Processing and AI-Based Damage Detection
*Takeshi Nagami1, Kobayashi Hiroyuki1 (1. TechnoHighway Co.)
[CS14-80]Multi-label Classification of Bridge Bearing Damage Using Vision Transformer
*Kanata Akaishi1, Ji Dang1, Hiroyuki Aoyagi2, Zou Rongzhi2 (1. Saitama University, 2. Kawakin Core Tech)
[CS14-81]Seismic Damage Assessment Method for RC Bridge Piers Using YOLO
*Tomoya Yoshida1, Ji Dang1 (1. Saitama University)
[CS14-82]Basic research on estimating the progression of bending damage in reinforced concrete beams using reinforcement learning
*Kiyohisa FUKUE Fukue1 (1. Knowledge Fusion Co.,Ltd.)
