A Pulse-Coupled Neural Network as A Simplified Bottom-Up Visual Attention Model
Marcos G. Quiles, Roseli Aparecida Francelin Romero, Liang Zhao · 2006
This work presents a bottom-up visual attention model based on a Pulse-Coupled Neural Network for scene segmentation. Each object in a given scene is represented by a synchronized pulse train, while different objects fire at different phases. Taking this into account, the model focuses on one object at a time. Using this model, the limit of linear non-separability can be easily overcome and computer simulations show its good performance.