Linlin Huang

China University of Mining and Technology

Papers

Total Citations

H-Index

About

Linlin Huang is a leading researcher in intelligent mining and computer vision, with a primary focus on automating coal and gangue separation to enhance energy efficiency and environmental sustainability. Her most cited work, "Coal and Gangue Separating Robot System Based on Computer Vision" (2021, 45 citations), pioneered a robotic system that uses visual recognition to distinguish coal from waste rock, directly addressing the challenge of improving coal quality while reducing pollution. This system not only boosts resource utilization but also enables the reuse of separated gangue, aligning with clean energy goals. In her follow-up study, "Construction of intelligent visual coal and gangue separation system based on CoppeliaSim" (2020, 9 citations), Huang advanced the field by simulating intelligent separation processes, laying groundwork for fully automated mining operations. Her contributions are critical to China’s energy strategy, where coal remains a dominant resource. By integrating robotics and computer vision, Huang is transforming traditional mining into a smarter, greener industry, with her work cited as a benchmark for future innovations in mineral processing and environmental protection.