Taewook Park
Papers
1
Total Citations
3
H-Index
1
About
Taewook Park is a researcher at the forefront of computer vision and embedded AI, with a focus on real-time localization and neural network optimization. His most-cited work, “Detection of Fiducial Marker With Neural Network Compression” (2023), addresses a critical challenge in augmented reality (AR), virtual reality (VR), PCB manufacturing, and robotics: achieving fast, highly accurate camera positioning using fiducial markers. Park’s key contribution lies in compressing neural networks to enable efficient marker detection on resource-constrained devices, bridging the gap between deep learning accuracy and real-time performance. This work has already garnered 3 citations, signaling early impact in a field where speed and precision are paramount. By tackling the computational bottlenecks of traditional marker detection, Park’s research promises to enhance the reliability of AR/VR experiences, streamline automated factory processes, and improve robot localization. His innovative approach to model compression not only advances practical applications but also sets a foundation for future work in lightweight, deployable AI systems. For students and researchers, Park’s work exemplifies how targeted neural network optimization can unlock new possibilities in real-world computer vision.
Research Focus
Key Achievements
Top Papers
- 1Detection of Fiducial Marker With Neural Network Compression3 citations · 2023