Name
Abstract | ||
|---|---|---|
The architecture of a complete image segmentation system and the development of an embedded VLSI low-power integrated circuit are reported. A neuromorphic engineering approach is adopted, with the purpose of reproducing behaviour of biological neural networks by taking advantage of the microelectronic implementation properties, especially low power consumption and reduced volume and weight. The system is divided in parallel-processing stages. After phototransduction, nonlinear filtering is applied to the image. Then, segmentation is performed and an output stage delivers segmentation and object properties information. Each stage is briefly described and simulations and experimental results are shown. The final goal is to develop a single-chip integrated system that performs all the described operations in focal-plane. |
Year | Venue | Keywords |
|---|---|---|
2004 | ESANN | image segmentation,parallel processing,integrated circuit,nonlinear filter,chip,integrable system,neural network |
Field | DocType | Citations |
Computer vision,Segmentation,Microelectronics,Computer science,Neuromorphic engineering,Property (programming),Image segmentation,Artificial intelligence,Artificial neural network,Integrated circuit,Very-large-scale integration,Machine learning | Conference | 2 |
PageRank | References | Authors |
0.49 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jordi Madrenas | 1 | 150 | 27.87 |
| Jordi Cosp | 2 | 36 | 6.25 |
| Lucas Oscar | 3 | 2 | 0.49 |
| Eduard Alarcón | 4 | 391 | 64.43 |
| Eva Vidal | 5 | 26 | 6.97 |
| Gerard Villar | 6 | 26 | 7.10 |