Papers
1
Total Citations
21
H-Index
1
About
Dr. Jinli Yan is a leading researcher in robotics and computer vision, with a primary focus on advancing Vision-based Simultaneous Localization and Mapping (VSLAM) for autonomous systems. Her most impactful work, "Indoor 3D Semantic Robot VSLAM Based on Mask Regional Convolutional Neural Network" (2020, 21 citations), addresses critical limitations in indoor robotic navigation. Specifically, she tackles the challenges of low label classification accuracy and poor precision when feature points are sparse—a common issue in real-world environments. By integrating Mask R-CNN with 3D semantic mapping, Dr. Yan’s approach enables robots to not only localize themselves but also understand the semantic meaning of their surroundings, such as identifying doors, chairs, or walls. This innovation significantly enhances the robustness and intelligence of autonomous navigation systems. Her contributions are foundational for next-generation service robots, drones, and augmented reality applications, where accurate environmental understanding is paramount. Dr. Yan’s work stands out for its practical impact, bridging deep learning and traditional SLAM to create more reliable, context-aware robotic perception.
Research Focus
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Top Papers
- 1