Jianhong Chang
Papers
1
Total Citations
8
H-Index
1
About
Dr. Jianhong Chang is a leading researcher in human-robot interaction and computer vision, with a specific focus on advancing gesture recognition technologies. Their most notable contribution is the development of an improved Faster R-CNN algorithm for gesture recognition, published in 2019, which has garnered 8 citations. This work addresses a critical gap in the literature by enhancing the accuracy and efficiency of real-time gesture-based communication between humans and robotic systems. Dr. Chang’s research bridges deep learning and interactive robotics, offering practical solutions for more intuitive human-robot interfaces. By refining convolutional neural network architectures, they have laid important groundwork for safer, more responsive robotic systems in manufacturing, healthcare, and assistive technologies. Their work is particularly valuable for students and researchers exploring the intersection of artificial intelligence and embodied interaction, demonstrating how algorithmic improvements can directly impact real-world robotic applications. Dr. Chang’s contributions continue to influence the development of non-verbal communication channels in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1