Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Over the past few years, Spiking Neural Networks (SNNs) have become popular as a
possible pathway to enable low-power event-driven neuromorphic hardware. However, their …

Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference
because the neurons in the networks are sparsely activated and computations are event …

Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …

Spiking neural networks (SNNs) are promising in ascertaining brain-like behaviors since
spikes are capable of encoding spatio-temporal information. Recent schemes, eg, pre …

Deep neural networks such as Convolutional Networks (ConvNets) and Deep Belief
Networks (DBNs) represent the state-of-the-art for many machine learning and computer …

The best performing learning algorithms devised for event cameras work by first converting
events into dense representations that are then processed using standard CNNs. However …