Yasutoshi Nomura
Papers
1
Total Citations
15
H-Index
1
About
Yasutoshi Nomura is a leading researcher in the application of deep learning and unmanned aerial vehicles (UAVs) to civil infrastructure monitoring. His primary research areas include computer vision, structural health monitoring, and automated defect detection. Nomura’s most impactful work, "Concrete Crack Detection Using UAV and Deep Learning" (2019, 15 citations), addresses the critical shortage of experienced inspection engineers by developing a fully automated system that combines drone imagery with convolutional neural networks. This contribution is pivotal for the non-destructive evaluation of aging bridges, tunnels, and roads, enabling faster, safer, and more consistent inspections than traditional manual methods. By integrating UAV technology with state-of-the-art deep learning, Nomura has helped pioneer a scalable solution for maintaining aging infrastructure worldwide. His work is particularly notable for its practical focus on real-world deployment, bridging the gap between academic computer vision and field-ready engineering tools. With growing citation impact, Nomura continues to advance the reliability and efficiency of automated visual inspection systems.
Research Focus
Key Achievements
Top Papers
- 1Concrete Crack Detection Using UAV and Deep Learning15 citations · 2019