Zheng Yong

Papers

Total Citations

H-Index

About

Zheng Yong is a researcher in computer vision and pattern recognition, with a primary focus on video-based human action recognition. His work addresses the challenge of accurately identifying and classifying human movements from video data—a technology with significant commercial value in areas such as surveillance, human-computer interaction, and automated video analysis. Yong’s major contribution lies in developing a multifeature fusion approach that leverages key frames to improve action recognition performance. By strategically selecting and combining multiple visual features from the most informative frames, his method enhances both efficiency and accuracy, reducing computational overhead while maintaining robust recognition capabilities. His most-cited paper, "Multifeature fusion action recognition based on key frames" (2021), has accumulated 9 citations, reflecting its relevance in a competitive and rapidly evolving field. This work has been recognized for its practical potential, offering a streamlined solution that balances feature richness with processing speed. Yong’s research continues to push forward the boundaries of video understanding, making him a notable contributor to the advancement of intelligent vision systems.