Jordi Cosp
Papers
1
Total Citations
5
H-Index
1
About
Jordi Cosp is a researcher whose work sits at the intersection of neuromorphic engineering and computer vision, with a particular focus on spiking neural networks (SNNs) for image processing. His most notable contribution is the development of a compact, scalable neuromorphic architecture that implements LEGION (Locally Excitatory Globally Inhibitory Oscillator Network)-based image segmentation using normalized synaptic weights. This work, published in 2019, has garnered 5 citations and represents a significant step toward efficient, biologically inspired visual processing systems. By leveraging the temporal dynamics of SNNs, Cosp’s approach enables robust segmentation while maintaining hardware efficiency—a critical advancement for real-time and low-power applications. His research bridges the gap between theoretical neuroscience and practical hardware design, offering a pathway to neuromorphic chips that can perform complex perceptual tasks. Cosp’s contributions are particularly relevant for students and researchers exploring event-driven computation, as his work demonstrates how normalized synaptic weights can stabilize network dynamics and improve segmentation accuracy. Through his innovative integration of neural coding principles with VLSI implementation, Jordi Cosp continues to push the boundaries of what is possible in neuromorphic vision systems.
Research Focus
Key Achievements
Top Papers
- 1