Yurong Du
Papers
4
Total Citations
88
H-Index
4
About
Yurong Du is a leading researcher at the intersection of computer vision, agricultural automation, and intelligent robotics. Their work focuses on developing lightweight, real-time object detection models—primarily based on the YOLO (You Only Look Once) architecture—to solve practical challenges in both agriculture and industrial inspection. Du’s most cited paper, “Apple rapid recognition and processing method based on an improved version of YOLOv5” (2023, 29 citations), demonstrates a high-speed system for fruit detection, enabling efficient automated harvesting. They extended this approach to agriculture with “A lightweight model based on YOLO for pomegranate before fruit thinning in complex environment” (2024, 23 citations), addressing the need for precise, real-time detection in dense, unstructured orchard settings. In parallel, Du has made significant contributions to industrial robotics, notably through “A wall climbing robot based on machine vision for automatic welding seam inspection” (2024, 20 citations) and “Weld Seam Tracking and Detection Robot Based on Artificial Intelligence Technology” (2023, 16 citations). These works integrate deep learning with robotic mobility, creating autonomous systems that climb vertical surfaces to detect and track weld seams, dramatically improving safety and efficiency in large-scale equipment maintenance. With a growing citation record, Du’s research is shaping the future of smart agriculture and intelligent industrial inspection.
Research Focus
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Top Papers
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