Papers
2
Total Citations
28
H-Index
2
About
Xiayang Qin is a rising researcher in agricultural robotics and computer vision, with a focus on developing intelligent systems for precision harvesting and robotic manipulation. His work bridges deep learning and practical automation, addressing critical challenges in detection and grasp planning for agricultural environments. In his highly cited 2024 paper, "DSNet: Double Strand Robotic Grasp Detection Network Based on Cross Attention," Qin introduced a novel architecture that integrates a transformer branch with a U-Net branch to reconcile local and global feature extraction, significantly improving robotic grasp detection. This work has already garnered 18 citations, reflecting its impact on the field. More recently, in 2025, Qin developed an optimized YOLO-PP-based cherry tomato detection system for autonomous precision harvesting, achieving 10 citations. This study tackles the complexity of detecting clustered cherry tomatoes in high-yield greenhouse settings, enhancing both accuracy and efficiency for automated harvesting robots. Qin’s contributions are pivotal for advancing smart agriculture, and his innovative approaches continue to inspire further research in robotic perception and autonomous farming systems.
Research Focus
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Top Papers
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