Papers
1
Total Citations
7
H-Index
1
About
Likai Ju is a researcher focused on advancing mechanical safety through intelligent sensing and computer vision technologies. His primary research areas include human-machine interaction safety, depth-sensing systems, and real-time hazard detection in industrial environments. Ju’s most cited work, “Human Position Detection Based on Depth Camera Image Information in Mechanical Safety” (2022), addresses a critical gap in traditional safety devices—such as light curtains and laser scanners—which can be easily bypassed and fail to distinguish humans from equipment. By leveraging depth camera data, Ju proposed a more robust method for detecting human presence and position, significantly reducing false negatives in safety-critical settings. This contribution has garnered 7 citations, reflecting its relevance to ongoing efforts in industrial automation and occupational safety. Ju’s research stands out for its practical approach to overcoming limitations of conventional sensors, offering a pathway toward smarter, more reliable safety systems. His work is particularly valuable for engineers and researchers developing next-generation protective measures in manufacturing and robotics.
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Top Papers
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