Chenghao Hua

Beijing Technology and Business University, Beijing Institute of Technology

Papers

Total Citations

H-Index

About

Chenghao Hua is a researcher working at the intersection of computer vision, intelligent agriculture, and robotic systems. His work spans two primary domains: smart agricultural technology and robotic vision stabilization, with a focus on applying deep learning and image processing to solve real-world challenges in precision farming and autonomous systems. Hua's most impactful contribution to date is his 2024 paper introducing a novel object detection framework leveraging diffused graphic large selective kernels combined with a one-to-few labelling strategy, specifically designed to detect small-scaled crop diseases with high accuracy — a critical capability for Intelligent Agriculture Management Systems integrated with IoT and edge computing platforms. This work has already garnered 6 citations within its first year, reflecting strong community interest. His earlier research on hybrid image stabilization for robotic bionic eyes (2018, 4 citations) demonstrated his versatility, addressing the challenge of motion-induced image blur in robotic vision through combined mechanical and electronic compensation techniques. More recently, his GDMR-Net architecture introduced multi-crossed attention mechanisms and rotation-aware annotations for agronomic detection tasks, reinforcing his commitment to advancing supply chain security in smart agriculture. Hua's research positions him as an emerging contributor to AI-driven precision agriculture and intelligent robotic perception systems.