Yaoheng Su
Papers
5
Total Citations
114
H-Index
5
About
Yaoheng Su is a researcher specializing in computer vision, deep learning-based object detection, and intelligent robotic systems, with particular expertise in agricultural automation and industrial inspection technologies. Su's work centers on adapting and optimizing state-of-the-art detection frameworks — most notably the YOLO family of models — to solve real-world challenges in complex, dynamic environments. Among Su's most impactful contributions is a series of innovations in automated weld seam inspection, including the development of wall-climbing robots equipped with machine vision capabilities for detecting vulnerabilities in large-scale special equipment. These systems address critical industrial safety concerns by replacing time-consuming manual inspection methods with intelligent, autonomous alternatives. Su has also made notable strides in precision agriculture, developing lightweight and improved YOLO-based models for apple recognition and pomegranate fruit-thinning detection under complex field conditions, advancing the feasibility of smart farming technologies. With a growing body of work accumulating over 110 citations across just a handful of recent publications — including a 2023 apple recognition paper with 29 citations and a 2024 welding inspection study with 26 — Su has rapidly established a reputation for producing practically impactful, highly cited research at the intersection of artificial intelligence, robotics, and real-world automation.
Research Focus
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Top Papers
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