This article presents the first keyword spotting (KWS) IC which uses a
r...
Standard dynamic vision sensor (DVS) event cameras output a stream of
sp...
The stomatopod (mantis shrimp) visual system has recently provided a
blu...
Long Short-Term Memory (LSTM) recurrent networks are frequently used for...
Dynamic vision sensor event cameras produce a variable data rate stream ...
Low-latency, low-power portable recurrent neural network (RNN) accelerat...
To help meet the increasing need for dynamic vision sensor (DVS) event c...
Neuromorphic event cameras are useful for dynamic vision problems under
...
The energy consumed by running large deep neural networks (DNNs) on hard...
Novel vision sensors such as event cameras provide information that is n...
Lower leg prostheses could improve the lives of amputees by increasing
c...
Deep-learning is a cutting edge theory that is being applied to many fie...
Mobile and embedded applications require neural networks-based pattern
r...
Event cameras are bio-inspired sensors that work radically different fro...
We present the first event-based learning approach for motion segmentati...
Machine vision systems using convolutional neural networks (CNNs) for ro...
Dynamic Vision Sensors (DVS), which output asynchronous log intensity ch...
Event cameras, such as dynamic vision sensors (DVS), and dynamic and
act...
Rapid and low power computation of optical flow (OF) is potentially usef...
Convolutional neural networks (CNNs) have become the dominant neural net...
Many neural networks exhibit stability in their activation patterns over...
New vision sensors, such as the Dynamic and Active-pixel Vision sensor
(...
Deep spiking neural networks (SNNs) hold great potential for improving t...
Event cameras are bio-inspired vision sensors that output pixel-level
br...
This paper describes the application of a Convolutional Neural Network (...