Visual scale independence in a network of spiking neurons

The scale independence in visual recognition tasks is still one big problem in neurocomputing today. This paper presents a method of obtaining scale independence in a purely feed-forward way, being able to account for ultra-rapid visual categorization. It used a retinotopic architecture of simple spiking neurons with different types of receptive fields, organized in a hierarchical fashion similar to the mammal visual path. Fast shunting inhibition had been implemented using a rank-order coding similar to that described by Thorpe and Gautrais (1998). Scale independence had been achieved by using different sized end-stopping bar detectors and combining them in a scalable way to produce scale independent response over a given domain. This solution does not conflict with the saliency based models and offers a great robustness to clutter.