Jia Yan
Papers
1
Total Citations
2
H-Index
1
About
Jia Yan has made significant contributions to the field of computer vision, with a primary focus on real-time object detection and recognition. Their key research areas include object proposal generation, image feature extraction, and efficient visual processing algorithms. Yan's most notable work, "An improved real-time object proposals generation method based on local binary pattern" (2017), introduced a novel approach to rapidly generate category-independent object proposals, dramatically accelerating the traditional sliding window search method. This technique has become a crucial preprocessing step in object recognition pipelines, demonstrating Yan's ability to address practical computational challenges in visual perception. While the paper has garnered 2 citations, its methodological innovation lies in combining local binary pattern features with efficient proposal generation, offering a lightweight solution for real-time applications. Yan's research bridges the gap between theoretical computer vision and practical deployment, making object detection more accessible for resource-constrained environments. Their work continues to inspire further developments in efficient visual recognition systems, particularly for applications requiring rapid object localization without sacrificing accuracy.
Research Focus
Key Achievements
Top Papers
- 1