This paper presents a sparse Change-Based Convolutional Long Short-Term
...
This article presents the first keyword spotting (KWS) IC which uses a
r...
Silicon cochlea designs capture the functionality of the biological coch...
Reducing energy consumption is a critical point for neural network model...
Deep Neural Networks, particularly Convolutional Neural Networks (ConvNe...
Including local automatic gain control (AGC) circuitry into a silicon co...
Event cameras report local changes of brightness through an asynchronous...
Spiking silicon cochlea sensors encode sound as an asynchronous stream o...
Long Short-Term Memory (LSTM) recurrent networks are frequently used for...
Operations typically used in machine learning al-gorithms (e.g. adds and...
Low-latency, low-power portable recurrent neural network (RNN) accelerat...
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...
The hardware and software foundations laid in the first half of the 20th...
Beamforming has been extensively investigated for multi-channel audio
pr...
Mobile and embedded applications require neural networks-based pattern
r...
Recurrent neural networks can be difficult to train on long sequence dat...
Plain recurrent networks greatly suffer from the vanishing gradient prob...
Event cameras, such as dynamic vision sensors (DVS), and dynamic and
act...
Recent work on encoder-decoder models for sequence-to-sequence mapping h...
Convolutional neural networks (CNNs) have become the dominant neural net...
Many neural networks exhibit stability in their activation patterns over...
Recurrent Neural Networks (RNNs) produce state-of-art performance on man...
There is an urgent need for compact, fast, and power-efficient hardware
...
The performance of automatic speech recognition systems under noisy
envi...
A striking difference between brain-inspired neuromorphic processors and...