Jing-Hao Sun

Papers

Total Citations

115

H-Index

About

Jing-Hao Sun is a leading researcher in computer vision and human-computer interaction, with a primary focus on advancing hand gesture recognition technologies. His most-cited work, "Research on the Hand Gesture Recognition Based on Deep Learning" (2018, 115 citations), addresses the growing demand for intuitive human-machine interfaces by leveraging deep learning to interpret complex hand gestures. This research has significant implications for practical applications, including robot control and intelligent furniture, where enriched gesture-based communication enhances user experience and system responsiveness. Sun’s contributions are foundational in bridging the gap between visual data processing and real-world interactive systems, demonstrating how deep learning models can achieve robust recognition under varied conditions. His work not only advances the theoretical understanding of gesture recognition but also provides actionable frameworks for deploying these systems in smart environments. With over 115 citations, his research has influenced subsequent studies in human-robot collaboration and ambient intelligence, cementing his role as a key innovator in making technology more accessible and responsive to natural human behaviors.