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08/22/2023
3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network
This paper presents a sparse Change-Based Convolutional Long Short-Term ...
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08/01/2022
A 23 μW Keyword Spotting IC with Ring-Oscillator-Based Time-Domain Feature Extraction
This article presents the first keyword spotting (KWS) IC which uses a r...
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06/06/2022
Continuous-Time Analog Filters for Audio Edge Intelligence: Review and Analysis on Design Techniques
Silicon cochlea designs capture the functionality of the biological coch...
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04/04/2022
Optimizing the Consumption of Spiking Neural Networks with Activity Regularization
Reducing energy consumption is a critical point for neural network model...
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03/29/2022
Kernel Modulation: A Parameter-Efficient Method for Training Convolutional Neural Networks
Deep Neural Networks, particularly Convolutional Neural Networks (ConvNe...
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02/14/2022
Spiking Cochlea with System-level Local Automatic Gain Control
Including local automatic gain control (AGC) circuitry into a silicon co...
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02/10/2022
Exploiting Spatial Sparsity for Event Cameras with Visual Transformers
Event cameras report local changes of brightness through an asynchronous...
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02/07/2022
T-NGA: Temporal Network Grafting Algorithm for Learning to Process Spiking Audio Sensor Events
Spiking silicon cochlea sensors encode sound as an asynchronous stream o...
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08/04/2021
Spartus: A 9.4 TOp/s FPGA-based LSTM Accelerator Exploiting Spatio-temporal Sparsity
Long Short-Term Memory (LSTM) recurrent networks are frequently used for...
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06/23/2021
Prospects for Analog Circuits in Deep Networks
Operations typically used in machine learning al-gorithms (e.g. adds and...
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12/25/2020
EdgeDRNN: Recurrent Neural Network Accelerator for Edge Inference
Low-latency, low-power portable recurrent neural network (RNN) accelerat...
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05/18/2020
DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction
Neuromorphic event cameras are useful for dynamic vision problems under ...
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03/29/2020
Data-Driven Neuromorphic DRAM-based CNN and RNN Accelerators
The energy consumed by running large deep neural networks (DNNs) on hard...
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03/24/2020
Exploiting Event Cameras by Using a Network Grafting Algorithm
Novel vision sensors such as event cameras provide information that is n...
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02/08/2020
Recurrent Neural Network Control of a Hybrid Dynamic Transfemoral Prosthesis with EdgeDRNN Accelerator
Lower leg prostheses could improve the lives of amputees by increasing c...
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11/05/2019
Thermodynamic Computing
The hardware and software foundations laid in the first half of the 20th...
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09/29/2019
FaSNet: Low-latency Adaptive Beamforming for Multi-microphone Audio Processing
Beamforming has been extensively investigated for multi-channel audio pr...
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05/06/2019
Closing the Accuracy Gap in an Event-Based Visual Recognition Task
Mobile and embedded applications require neural networks-based pattern r...
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01/22/2019
Reducing state updates via Gaussian-gated LSTMs
Recurrent neural networks can be difficult to train on long sequence dat...
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01/18/2018
Overcoming the vanishing gradient problem in plain recurrent networks
Plain recurrent networks greatly suffer from the vanishing gradient prob...
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11/04/2017
DDD17: End-To-End DAVIS Driving Dataset
Event cameras, such as dynamic vision sensors (DVS), and dynamic and act...
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08/03/2017
Sensor Transformation Attention Networks
Recent work on encoder-decoder models for sequence-to-sequence mapping h...
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06/05/2017
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Convolutional neural networks (CNNs) have become the dominant neural net...
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12/16/2016
Delta Networks for Optimized Recurrent Network Computation
Many neural networks exhibit stability in their activation patterns over...
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08/24/2016
Recurrent Neural Networks With Limited Numerical Precision
Recurrent Neural Networks (RNNs) produce state-of-art performance on man...
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06/23/2016
Precise deep neural network computation on imprecise low-power analog hardware
There is an urgent need for compact, fast, and power-efficient hardware ...
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06/22/2016
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition
The performance of automatic speech recognition systems under noisy envi...
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06/10/2015
