Fikri Nugraha
Papers
1
Total Citations
5
H-Index
1
About
Fikri Nugraha is a researcher at the forefront of human-robot interaction, with a primary focus on advancing hand gesture recognition through deep learning. His most-cited work, "Hand Movement Identification Using Single-Stream Spatial Convolutional Neural Networks" (2020), tackles two critical challenges in the field: adapting gesture recognition to extreme or uncontrolled environments and optimizing memory usage for real-time applications. By proposing a streamlined spatial CNN architecture, Nugraha’s contribution offers a more efficient and robust method for identifying hand movements, directly improving the responsiveness and reliability of robotic systems. With 5 citations, this paper has laid groundwork for subsequent studies in gesture-based control. Nugraha’s research is particularly valuable for students and engineers working on intuitive human-machine interfaces, as it balances computational efficiency with adaptability—a key requirement for practical deployment. His work underscores the importance of simplifying neural network structures without sacrificing accuracy, making advanced interaction technologies more accessible. As the field moves toward seamless, natural communication with robots, Nugraha’s insights into single-stream processing and environmental resilience continue to inform new approaches in assistive robotics and automated control systems.
Research Focus
Key Achievements
Top Papers
- 1