Hyunjong Cho

Papers

Total Citations

H-Index

About

Hyunjong Cho is a researcher whose work bridges computer vision and embedded systems, with a particular focus on efficient, real-time face recognition for robotic applications. His most-cited paper, "PCA-based face recognition in an embedded module for robot application" (2009), demonstrates a key contribution: the implementation of a principal component analysis (PCA)-based face recognition algorithm on an ARM CPU embedded module. By optimizing this computationally intensive task for a resource-constrained platform, Cho showed that recognition could be achieved with significantly improved processing time while maintaining accuracy, as validated using the Yale face database. This work is notable for its practical orientation, targeting the integration of vision capabilities directly into robotic hardware rather than relying on off-board processing. While his citation count (2) reflects a niche but focused impact, Cho’s research addresses a critical challenge in autonomous systems: enabling real-time, on-device perception. His approach offers a blueprint for deploying machine learning in embedded environments, making his contributions valuable for students and engineers working at the intersection of robotics, low-power computing, and efficient algorithm design.