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Found 2 papers, 1 papers with code
Optimized spiking neurons classify images with high accuracy through temporal coding with two spikes
Spike-based neuromorphic hardware promises to reduce the energy consumption of image classification and other deep learning applications, particularly on mobile phones or other edge devices.
Recognizing Images with at most one Spike per Neuron
We introduce a new conversion method where a gate in the ANN, which can basically be of any type, is emulated by a small circuit of spiking neurons, with At Most One Spike (AMOS) per neuron.
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