Ilayda Yaman
Papers
2
Total Citations
7
H-Index
2
About
Ilayda Yaman is a researcher at the forefront of multisensory fusion for indoor localization, with a focus on integrating vision, radio, and audio data to achieve robust positioning in complex environments. Her major contribution is the creation of the LuViRA (Lund University Vision, Radio, and Audio) Dataset, a synchronized multisensory resource that includes color images, depth maps, inertial measurement unit (IMU) readings, and 5G massive MIMO channel responses. This dataset addresses a critical gap in the field by providing aligned data from diverse sensors, enabling the development of more accurate and resilient localization algorithms. With a total of 7 citations across two versions of her work (2023 and 2024), Yaman’s dataset has already garnered attention for its potential to advance research in areas such as autonomous navigation, augmented reality, and smart environments. Her work stands out for its practical impact, offering a benchmark that bridges the gap between theoretical models and real-world deployment. As a researcher at Lund University, Yaman is helping to shape the future of indoor positioning systems, making her a notable contributor to the growing field of sensor fusion and 5G-enabled localization.
Research Focus
Key Achievements
Top Papers
- 1
- 2