Eiichi Yamashina
Papers
2
Total Citations
6
H-Index
2
About
Eiichi Yamashina is a leading researcher in the field of electrical infrastructure inspection, specializing in the application of computer vision and edge computing for power transmission line (PTL) maintenance. His work focuses on overcoming the limitations of traditional inspection methods—such as line crawling, robots, and helicopters—by deploying lightweight, real-time object detection models on single-board computers. Yamashina’s major contributions include the adaptation of YOLO architectures, notably YOLOv3 and YOLOv7, for detecting critical PTL components like insulators and dampers directly on resource-constrained platforms such as the Raspberry Pi. His 2023 paper on YOLOv3 implementation has garnered 4 citations, while his subsequent 2024 work advancing YOLOv7 on single-board computers has already attracted 2 citations, reflecting growing interest in cost-effective, automated inspection solutions. By enabling on-device analysis without cloud dependency, Yamashina’s research promises to make PTL monitoring faster, safer, and more accessible, reducing downtime and preventing outages. His work stands at the intersection of deep learning and embedded systems, offering a scalable path toward smarter, more resilient energy grids.
Research Focus
Key Achievements
Top Papers
- 1
- 2