Kaito Kosuge
Papers
1
Total Citations
4
H-Index
1
About
Kaito Kosuge is a researcher at the forefront of applying deep learning to infrastructure inspection, with a particular focus on the automated detection of corrosion in critical pipeline systems. His most-cited work, "Detection of Rust from Images in Pipes Using Deep Learning" (2021), addresses the urgent challenge of aging sewage infrastructure by developing a method that enables earthworm-type inspection robots to autonomously identify rust and degradation from internal pipe imagery. This contribution is vital for moving beyond manual, time-consuming inspections toward safer, more efficient, and scalable monitoring solutions. With 4 citations, his paper has already established a foundation for integrating computer vision with robotic inspection in civil engineering. Kosuge’s research sits at the intersection of deep learning, robotics, and structural health monitoring, offering practical tools to extend the lifespan of critical urban infrastructure. His work is particularly notable for its direct application to real-world problems, demonstrating how AI can enhance the safety and longevity of essential public systems.
Research Focus
Key Achievements
Top Papers
- 1Detection of Rust from Images in Pipes Using Deep Learning4 citations · 2021