Umme Salma

World University of Bangladesh

Papers

1

Total Citations

23

H-Index

1

About

Umme Salma is a researcher at the intersection of computer vision and industrial automation, with a primary focus on developing intelligent robotic systems for manufacturing. Her most significant contribution is the design and implementation of a computer vision-based industrial robotic arm capable of autonomously sorting objects by color and height—a breakthrough that directly addresses the labor-intensive and time-consuming nature of manual sorting in production lines. This work, published in 2020 and garnering 23 citations, demonstrates her ability to solve real-world industrial challenges by integrating visual perception with robotic control. By automating a task that traditionally requires numerous human workers, Salma’s research not only enhances efficiency but also reduces operational costs and human error in manufacturing environments. Her approach showcases a practical application of AI and robotics, making her a notable figure in the field of industrial automation. For students and researchers, her work serves as an inspiring example of how computer vision can be leveraged to create tangible, impactful solutions for industry, bridging the gap between academic research and real-world production needs.

Research Focus

Key Achievements

1
H-Index
1
Papers
23
Total Citations
23
Avg Citations/Paper
🏆 Most Cited Paper
Computer Vision Based Industrial Robotic Arm for Sorting Objects by Color and Height
23 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: World University of Bangladesh

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago