Masahiro Korenaga
Papers
1
Total Citations
2
H-Index
1
About
Masahiro Korenaga’s research lies at the intersection of industrial safety, acoustic engineering, and autonomous robotics. His most notable contribution, “Acoustic Monitoring in Industrial Plants with Autoencoders and a Mobile Robot” (2023), pioneers the use of deep learning—specifically autoencoders—to detect abnormal sounds in complex environments like refineries. By integrating this acoustic anomaly detection system into a mobile robot, Korenaga addresses a critical gap in industrial inspection: the need for continuous, automated monitoring that reduces reliance on human field operators. This work has garnered early attention with 2 citations, signaling its potential to reshape predictive maintenance protocols. Korenaga’s approach combines real-world practicality with cutting-edge AI, offering a scalable solution for hazardous plant environments. His research not only enhances operational safety but also lays groundwork for future autonomous inspection systems, making him a rising voice in industrial robotics and machine learning applications.
Research Focus
Key Achievements
Top Papers
- 1