Papers
1
Total Citations
2
H-Index
1
About
Xiaolong Ye is a researcher specializing in computer vision, robotics, and industrial automation, with a particular focus on integrating visual and thermal sensing for intelligent systems. His most notable contribution is the development of a visual saliency detection method for identifying over-temperature regions in 3D space using dual-source images, a technique that enables mobile robots to autonomously detect equipment temperature anomalies and navigate complex industrial environments. This work, published in 2020, has garnered 2 citations and represents a foundational step in combining thermal imaging with spatial awareness for predictive maintenance and safety monitoring. Ye’s research addresses critical challenges in human-robot interaction and autonomous inspection, bridging the gap between raw sensor data and actionable environmental understanding. His achievements include advancing the practical deployment of vision-based systems in hazardous or hard-to-reach industrial settings, where early detection of overheating components can prevent costly failures and accidents. By pioneering methods that fuse visual and thermal data streams, Xiaolong Ye is contributing to the next generation of intelligent, safety-conscious robotic systems.
Research Focus
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Top Papers
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