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Spike-Based MAX Networks for Nonlinear Pooling in Hierarchical Vision Processing
2007 / IEEE / 978-1-4244-1524-3
This item was taken from the IEEE Conference ' Spike-Based MAX Networks for Nonlinear Pooling in Hierarchical Vision Processing ' Complex cells in the visual cortex utilize a maximum (MAX) operation to pool the outputs of simple cells to achieve feature specificity and invariance. We demonstrate a biologically-plausible MAX network for nonlinear pooling in hardware, using a reconfigurable multichip address event representation based VLSI system. With this implementation we have shown that we can implement simple and advanced stages of visual processing on the same chip and are one step closer to constructing an autonomous, continuous-time, biologically-plausible hierarchical model of visual information processing using large-scale arrays of identical silicon neurons.
Large Scale Silicon Neuron Arrays
Spike Based Max Network
Hierarchical Vision Processing
Visual Cortex Cells
Biologically Plausible Max Network
Multichip Address Event Representation
Visual Information Processing
Biological System Modeling
Integrate-and-fire Array Transceiver
Reconfigurable Vlsi System