Papers
3
Total Citations
15
H-Index
2
About
Yunlong Pan is a researcher specializing in computer vision, robotics, and intelligent manufacturing, with a focus on real-time object detection and robotic manipulation in unstructured environments. His most notable contribution is the development of a hierarchical aggregated attention lightweight network for detecting camouflaged objects in complex, unstructured scenarios—a breakthrough that addresses critical challenges in autonomous surveillance and search-and-rescue operations, earning 10 citations since 2023. Pan also designed an industrial robot sorting system with visual guidance using Webots, applying Hu invariant moments for rapid static object recognition to improve production line efficiency. His recent work on object dynamic recognition and grasping introduces a lightweight semantic attention network with learnable boundary vectors, enabling robots to locate and manipulate objects with greater precision. With a growing citation record, Pan’s research bridges the gap between efficient neural architectures and practical robotic applications, making his work highly relevant for students and researchers in robotics, computer vision, and industrial automation.
Research Focus
Key Achievements
Top Papers
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