Papers
2
Total Citations
28
H-Index
2
About
Youngbae Hwang is a researcher whose work bridges computer vision and agricultural robotics, with a focus on precision agriculture and 3D sensing. His key research areas include object detection and pose estimation for agricultural applications, as well as multi-camera calibration for RGB-D systems. Hwang’s most notable contribution is in tomato pose estimation, where he developed a method using the association of tomato body and sepal to improve detection accuracy in complex greenhouse environments—a critical step toward automated harvesting. This work has already garnered 16 citations since its 2024 publication, reflecting its immediate relevance. His earlier work on multi-cue-based circle detection for robust extrinsic calibration of RGB-D cameras (2019, 12 citations) addresses a fundamental challenge in 3D vision: enabling multiple cameras to work together seamlessly for applications like 3D modeling and human-computer interaction. By minimizing calibration costs while maintaining accuracy, Hwang’s research has practical implications for robotics and automation. His contributions demonstrate a clear trajectory from foundational sensor calibration to applied agricultural robotics, making his work valuable for students and researchers interested in the intersection of computer vision, robotics, and smart farming.
Research Focus
Key Achievements
Top Papers
- 1Tomato pose estimation using the association of tomato body and sepal16 citations · 2024
- 2