Neuromorphic selective attention systems

Neuromorphic VLSI selective attention systems: from single chip solutions to multi-chip systems

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and...

A neuromorphic VLSI device for implementing 2D selective attention systems

Selective attention is a mechanism used to sequentially select and process salient subregions of the input space, while suppressing inputs arriving from nonsalient regions. By processing small amounts of sensory information in a serial fashion, rather than attempting to process all the sensory data in parallel, this mechanism overcomes the problem of flooding limited processing capacity systems...

A 2D Neuromorphic VLSI Architecture for Modeling Selective Attention

Selective attention is a mechanisms used to sequentially select the spatial locations of salient regions in the sensor’s field of view. This mechanism overcomes the problem of flooding limited processing capacity systems with sensory information. It is found in many biological sensory systems and can be a useful engineering tool for artificial visual systems. We present a hardware model of a se...

Evaluation of Selective Attention under Similarity Transforms

Computational selective attention systems have mostly been developed as models of human attention, and they have been evaluated on that basis. Now, however, they are being used as front ends to object recognition systems, and in particular to appearance-based recognition systems. As such, they need to be evaluated by other criteria. A common goal for object recognition systms in invariance to 2...