Papers
2
Total Citations
3
H-Index
1
About
Dae Seung Yoo is a researcher focused on advancing industrial automation and safety through artificial intelligence and next-generation communication technologies. His work centers on two key areas: AI-driven acoustic signal processing for equipment inspection, and humanless monitoring systems for hazardous industrial environments. In a notable contribution, Yoo developed a two-stage AI method for inspecting generator stator wedge fasteners, combining a CNN-based autoencoder for noise removal with a feature extraction classifier—a technique that promises to improve reliability in power generation maintenance. He also pioneered an industrial humanless monitoring system over 5G networks for shipyard environments, leveraging image-based worker recognition to enhance safety and efficiency in high-risk settings. Though early in his career, with papers accumulating citations since 2022 and 2024, Yoo’s research addresses pressing real-world challenges in Industry 4.0, demonstrating the practical integration of AI and 5G for smarter, safer factories. His work is particularly relevant for students and researchers interested in applied machine learning, industrial IoT, and the future of automated quality control.
Research Focus
Key Achievements
Top Papers
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