Majid Fasihiany
Papers
1
Total Citations
4
H-Index
1
About
Majid Fasihiany is a researcher at the forefront of applied computer vision and robotics, with a primary focus on developing cost-effective, real-time automation solutions for industrial logistics. His most notable contribution is the design and implementation of computer vision algorithms on a Raspberry Pi 4 for automated depalletizing—a system that detects and locates variable-shaped objects on a pallet to guide robotic unstacking. This work, published in 2024 and already garnering 4 citations, demonstrates his ability to bridge advanced algorithmic design with low-cost, accessible hardware, making automation feasible for smaller-scale manufacturing environments. Fasihiany’s research addresses critical challenges in object detection, localization, and real-time processing, offering a scalable alternative to expensive industrial systems. His impact lies in democratizing automation technology, enabling efficient depalletizing without prohibitive infrastructure costs. By combining robust computer vision techniques with edge computing, Fasihiany has opened new pathways for intelligent robotics in logistics, positioning his work as a practical and innovative contribution to the field.
Research Focus
Key Achievements
Top Papers
- 1