Sharda Vashisth
Papers
1
Total Citations
11
H-Index
1
About
Sharda Vashisth is a researcher in computer vision and intelligent transportation systems, with a primary focus on traffic sign recognition (TSR) for autonomous and assisted driving. Her most-cited work, "Histogram of Oriented Gradients Based Reduced Feature for Traffic Sign Recognition" (2018, 11 citations), addresses a critical challenge in the field: developing robust, computationally efficient TSR systems that can reliably interpret road signs in real-world conditions. By proposing a reduced feature extraction method based on Histogram of Oriented Gradients (HOG), Vashisth’s research contributes to making TSR more practical for deployment in vehicles, ultimately enhancing driver assistance and autonomous navigation safety. Her work sits at the intersection of computer vision, machine learning, and automotive safety, aiming to bridge the gap between academic algorithms and real-world application. With 11 citations, this paper has served as a reference for subsequent studies on efficient feature representation for traffic sign classification. Vashisth’s contributions are particularly relevant for students and researchers interested in low-complexity computer vision models, embedded systems for vehicles, and the broader goal of improving road safety through intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1