Tabassum Binth Yeahyea
Papers
1
Total Citations
51
H-Index
1
About
Tabassum Binth Yeahyea is a rising researcher at the intersection of computer vision and robotics, with a core focus on automating industrial and human-centric tasks through intelligent sensing and manipulation. Her most cited work, “Computer Vision-based Robotic Arm for Object Color, Shape, and Size Detection” (2022, 51 citations), exemplifies her key contribution: developing cost-effective, vision-guided robotic systems that can perceive and interact with their environment with high precision. By integrating real-time object detection algorithms with robotic control, she has addressed critical challenges in industrial automation—reducing human labor, production time, and operational risks while boosting efficiency. This work has been widely recognized for its practical applicability in smart manufacturing and logistics. Beyond this flagship paper, her research continues to explore how embedded vision and sensor fusion can make robots more adaptive and accessible. With her work already garnering significant attention in the robotics community, Tabassum is establishing herself as a promising voice in applied computer vision and automation, bridging the gap between laboratory innovation and real-world industrial solutions.
Research Focus
Key Achievements
Top Papers
- 1