Shanshan Jiao
Papers
1
Total Citations
5
H-Index
1
About
Dr. Shanshan Jiao is a researcher whose work sits at the intersection of computer vision and mobile robotics, with a particular focus on visual place recognition. Her most-cited paper, "Salient Feature Selection for CNN-Based Visual Place Recognition" (2018), addresses a critical bottleneck in deploying convolutional neural networks on mobile robots: the trade-off between recognition accuracy and real-time performance. By proposing a method to select only the most salient features from CNN representations, Dr. Jiao’s work enables robots to navigate large-scale, dynamic environments more efficiently, reducing computational overhead without sacrificing robustness. This contribution is especially valuable for autonomous systems that must operate under strict time and resource constraints. With 5 citations, her research has laid groundwork for more practical, real-world applications of deep learning in robotics. Dr. Jiao’s work exemplifies the kind of focused, problem-driven innovation that bridges the gap between high-performance algorithms and the physical limitations of mobile platforms—a crucial step toward truly autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1Salient Feature Selection for CNN-Based Visual Place Recognition5 citations · 2018