Papers
1
Total Citations
32
H-Index
1
About
Dr. Zeliang Zong is a leading researcher in remote sensing and artificial intelligence, with a primary focus on power infrastructure monitoring and UAV-based LiDAR data analysis. His most notable contribution is the development of DCPLD-Net, a diffusion coupled convolution neural network that enables real-time detection of power transmission lines from UAV-borne LiDAR data. This work, published in 2022 and garnering 32 citations, addresses the critical need for stable and reliable electric power supply by revolutionizing inspection methods. Dr. Zong’s research bridges deep learning and geospatial analysis, significantly improving the efficiency and accuracy of automated power line extraction—a vital task for maintaining social production and grid safety. His innovative approach integrates advanced neural architectures with remote sensing technologies, setting a new standard for real-time infrastructure monitoring. With growing recognition in the field, Dr. Zong’s contributions are shaping the future of smart grid maintenance and UAV-based environmental sensing, making him a key figure in applied AI for energy systems.
Research Focus
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Top Papers
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