Nazerke Kalidolda
Papers
3
Total Citations
18
H-Index
3
About
Nazerke Kalidolda is a researcher focused on human-robot interaction (HRI) and assistive robotics, with a particular emphasis on bridging communication gaps for hearing-impaired communities. Her work centers on developing intelligent robotic systems capable of real-time sign language interpretation, specifically targeting the recognition of Cyrillic manual alphabets and fingerspelling. Her most cited paper, "Cyrillic manual alphabet recognition in RGB and RGB-D data for sign language interpreting robotic system (SLIRS)" (2017, 8 citations), introduces a novel approach to integrating RGB and depth data for robust gesture recognition, laying the groundwork for a robotic interpreter that could operate in public spaces like banks and hospitals. In "Towards Interpreting Robotic System for Fingerspelling Recognition in Real Time" (2018, 5 citations), she advances this vision by focusing on real-time performance, while "Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces" (2017, 5 citations) explores how robots can dynamically adjust their behavior in crowded, multi-user environments. Collectively, her work has garnered 18 citations, reflecting its growing relevance in assistive robotics. Kalidolda’s contributions are notable for their practical, user-centered design, aiming to empower deaf-mute individuals through accessible, autonomous robotic assistance.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3