Neural model of visual selective attention for automatic translation invariant object recognition in cluttered images

This paper presents a biologically inspired neural model for detecting, locating and recognising all known objects in the visual scene automatically. In particular, this model employs bottom-up segmentation to achieve shifts in spatial attention, for selecting potential regions of interest across the visual scene.