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A neuromorphic categorization system with Online Sequential Extreme Learning
2014
2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings
This paper presents an event-driven categorization system which processes the address events from a Dynamic Vision Sensor. Using neuromorphic processing, cortex-like spike-based features are extracted by an event-driven MAX-like convolutional network. The extracted spike patterns are then classified by an Online Sequential Extreme Learning Machine with Auto Encoder. Using a Lookup Table, we achieve a virtually fully connected system by physically activating only a very small subset of the
doi:10.1109/biocas.2014.6981780
dblp:conf/biocas/DingZC14
fatcat:247gx2gckfc6bp43cqey2xv3fu