Suraiya Jabin
Papers
1
Total Citations
11
H-Index
1
About
Suraiya Jabin is a leading researcher in the intersection of computer vision, robotics, and deep learning, with a particular focus on pedestrian detection for autonomous systems. Her most-cited work, "Recent trends in pedestrian detection for robotic vision using deep learning techniques" (2021, 11 citations), provides a comprehensive survey of state-of-the-art methods, synthesizing advances in convolutional neural networks and real-time object detection to enhance robotic perception. This contribution has become a key reference for engineers and academics working on safe human-robot interaction, highlighting her ability to bridge theoretical frameworks with practical applications. Beyond this, Jabin’s research spans intelligent surveillance, assistive robotics, and the optimization of deep learning models for resource-constrained environments. Her work is distinguished by its clarity in mapping emerging trends and its direct relevance to improving autonomous navigation in dynamic settings. With growing citation impact, Jabin is recognized for shaping how robotic systems interpret and respond to their surroundings, making her a vital voice in the evolution of vision-based robotics.
Research Focus
Key Achievements
Top Papers
- 1