Qishen Lv

Papers

Total Citations

H-Index

About

Qishen Lv is a researcher whose work sits at the intersection of computer vision and intelligent industrial automation. His primary research focus is on developing deep learning-based algorithms to solve real-world challenges in power systems, particularly the automatic recognition of pointer-type meters in substations. Lv’s most cited paper, "A Pointer Meter Recognition Algorithm Based on Deep Learning" (2020, 32 citations), addresses a critical bottleneck in the transition to unmanned, intelligent substations: the low recognition accuracy of pointer meters during robotic inspection. By proposing a novel deep learning approach, his work directly improves the reliability of automated visual inspection, a key component of modern smart grid infrastructure. This contribution not only advances the field of applied computer vision but also has tangible implications for the safety and efficiency of power system operations. Lv’s research demonstrates a clear commitment to bridging the gap between algorithmic innovation and practical engineering deployment, making his work highly relevant for students and researchers interested in deep learning for industrial automation, smart grid technologies, and the real-world application of AI in critical infrastructure.