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Found 5 papers, 3 papers with code
Neural information coding for efficient spike-based image denoising
The neural coding schemes are then evaluated through experiments in terms of denoising performance and computation efficiency for a state-of-the-art deep convolutional neural network.
Object Detection with Spiking Neural Networks on Automotive Event Data
Based on these results, we combined our SNNs with SSD to propose the first spiking neural networks capable of performing object detection on the complex GEN1 Automotive Detection event dataset.
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Quantization and Deployment of Deep Neural Networks on Microcontrollers
The quantization methods, relevant in the context of an embedded execution onto a microcontroller, are first outlined.
Learning from Event Cameras with Sparse Spiking Convolutional Neural Networks
To design more efficient computer vision algorithms, we propose to follow an end-to-end biologically inspired approach using event cameras and spiking neural networks (SNNs).
Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence
Moreover, we propose modified versions of the standard Rate Coding technique to make trade-offs with the Time Coding paradigm, which is characterized by the low number of spikes propagating in the network.
