Tianhu Liu
Papers
2
Total Citations
120
H-Index
2
About
Tianhu Liu is a leading researcher in agricultural robotics and computer vision, specializing in automated fruit detection and localization for precision agriculture. His work focuses on developing advanced deep learning and image processing techniques to address the challenges of identifying and harvesting fruits in complex, natural environments. Liu’s major contributions include pioneering the use of binocular stereo vision combined with an improved YOLOv3 model for pineapple fruit detection and localization, achieving robust performance under varying lighting and occlusion conditions—a study that has garnered 79 citations. He also developed an innovative method for identifying immature and mature pomelo fruits using elliptical model fitting in the Cr–Cb color space, a foundational approach cited 41 times. These contributions have significantly advanced the field of smart farming, enabling more efficient and accurate robotic harvesting systems. Liu’s work is widely recognized for its practical applications in reducing labor costs and improving crop yield estimation, making him a key figure in the intersection of artificial intelligence and sustainable agriculture.
Research Focus
Key Achievements
Top Papers
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