Fearghal Morgan
Papers
1
Total Citations
4
H-Index
1
About
Fearghal Morgan is a leading researcher in embedded systems and real-time video processing, with a particular focus on hardware-efficient implementations for resource-constrained devices. His most-cited work, "Embedded Implementation of a Real-Time Motion Estimation Method in Video Sequences" (2016), tackles the critical challenge of gradient-based motion estimation—a computationally intensive task that traditionally limits deployment in compact, real-time applications. By developing a novel embedded architecture, Morgan demonstrated how to extract motion information from video signals with significantly reduced computing costs, enabling practical use in portable and low-power systems. This contribution has garnered attention in the field, with 4 citations reflecting its foundational role in advancing embedded vision technologies. Beyond this paper, Morgan’s research spans reconfigurable computing, FPGA-based design, and digital system optimization, often emphasizing bridging the gap between algorithmic complexity and hardware feasibility. His work is particularly valuable for students and researchers exploring real-time video analytics, autonomous systems, or IoT devices, where efficient motion estimation is key. Morgan’s achievements underscore a commitment to making sophisticated computer vision techniques accessible for real-world, embedded applications.
Research Focus
Key Achievements
Top Papers
- 1