V. Kavyasree
Papers
1
Total Citations
10
H-Index
1
About
V. Kavyasree is a researcher whose work centers on advancing human-computer interaction through innovative computer vision and deep learning techniques. Her primary research areas include dynamic hand gesture recognition, sign language interpretation, and motion analysis. Kavyasree’s most notable contribution is her development of a two-stream fusion model that integrates 3D-CNN and 2D-CNN architectures with optical flow-guided motion templates. This approach significantly improves the accuracy and robustness of dynamic hand gesture recognition, addressing critical challenges in real-world applications such as robotic surgery and assistive technologies. Her seminal paper on this model has garnered 10 citations, reflecting its growing influence in the field. By bridging the gap between spatial and temporal feature extraction, Kavyasree’s work provides a practical framework for more natural and intuitive human-computer interfaces. Her research not only advances technical methodologies but also holds promise for enhancing communication tools for the deaf and hard-of-hearing community. Kavyasree’s contributions underscore her commitment to developing accessible, real-time gesture recognition systems that can transform how humans interact with machines.
Research Focus
Key Achievements
Top Papers
- 1