Jae Min Cho

Korea University of Science and Technology

Papers

Total Citations

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About

Jae Min Cho is a researcher in robotics and computer vision, with a focus on enabling precise object detection and manipulation in industrial environments. His work addresses critical challenges in manufacturing automation, particularly the difficulty of applying object recognition technologies under real-world conditions where lighting, background complexity, and object shape can vary significantly. His most cited paper, "Precise object detection using local feature for robot manipulator" (2017, 6 citations), proposes a robust method for detecting objects by leveraging local features, improving the reliability of robot manipulators in dynamic settings. This contribution is notable for its practical implications in smart manufacturing and human-robot collaboration. Cho’s research bridges the gap between theoretical computer vision and applied robotics, offering solutions that enhance the adaptability and precision of automated systems. His work continues to influence the development of more resilient and context-aware robotic systems, making him a key figure in advancing industrial automation.