Md Fahim Shahoriar Titu
Papers
2
Total Citations
14
H-Index
2
About
Md Fahim Shahoriar Titu is a rising researcher at the intersection of artificial intelligence, robotics, and environmental sustainability. His primary research areas include deep learning for visual pollution detection, cooperative robotics, and computer vision applications in industrial and urban settings. Titu's most impactful contribution is his pioneering work on "Deep-Learning-Based Real-Time Visual Pollution Detection in Urban and Textile Environments" (2024), which has already garnered 10 citations. This study introduces an innovative approach combining deep learning networks with robotic vision systems and Google Street View to automatically identify and classify visual pollutants—from litter to aesthetic blights—in real time, offering a scalable solution for smart city management. In his earlier work, "Experiments with cooperative robots that can detect object’s shape, color and size to perform tasks in industrial workplaces" (2023, 4 citations), Titu demonstrated how multi-robot systems can collaboratively perceive and manipulate objects based on physical attributes, advancing human-robot collaboration in manufacturing. His research bridges the gap between environmental monitoring and autonomous systems, with potential applications in urban planning, textile industry quality control, and sustainable development. Titu's work is particularly notable for its practical, real-world focus, leveraging accessible technologies like Google Street View to tackle pervasive environmental challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2