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Mostrando ítems 1-10 de 13
Artículo
Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity
(IEEE Computer Society, 2019)
Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge devices is still challenging. Unlike the most state of the art inference engines which are efficient for static signals, our brain is ...
Ponencia
Learning weights with STDP to build prototype images for classification
(IEEE Computer Society, 2019)
The combination of Spike Timing Dependent Plasticity (STDP) and latency coding used in a spiking neural network has been shown to learn hierarchical features. In this paper we propose a new way to classify images using ...
Ponencia
Scene Context Classification with Event-Driven Spiking Deep Neural Networks
(IEEE Computer Society, 2018)
Event-Driven computation is attracting growing attention among researchers for several reasons. On one hand, the availability of new bio-inspired retina-like vision sensors that provide spiking outputs, like the Dynamic ...
Ponencia
Conversion of Synchronous Artificial Neural Network to Asynchronous Spiking Neural Network using sigma-delta quantization
(IEEE Computer Society, 2019)
Artificial Neural Networks (ANNs) show great performance in several data analysis tasks including visual and auditory applications. However, direct implementation of these algorithms without considering the sparsity of ...
Ponencia
Neocortical frame-free vision sensing and processing through scalable Spiking ConvNet hardware
(IEEE Computer Society, 2010)
This paper summarizes how Convolutional Neural Networks (ConvNets) can be implemented in hardware using Spiking neural network Address-Event-Representation (AER) technology, for sophisticated pattern and object recognition ...
Ponencia
Spiking Hough for Shape Recognition
(Springer, 2017)
The paper implements a spiking neural model methodology inspired on the Hough Transform. On-line event-driven spikes from Dynamic Vision Sensors are evaluated to characterize and recognize the shape of Poker signs. The ...
Artículo
A 1.5 ns OFF/ON Switching-Time Voltage-Mode LVDS Driver/Receiver Pair for Asynchronous AER Bit-Serial Chip Grid Links With Up to 40 Times Event-Rate Dependent Power Savings
(IEEE Computer Society, 2013)
This paper presents a low power fast ON/OFF switchable voltage mode implementation of a driver/receiver pair intended to be used in high speed bit-serial Low Voltage Differential Signaling (LVDS) Address Event ...
Ponencia
An Intrinsic Method for Fast Parameter Update on the SpiNNaker Platform
(IEEE Computer Society, 2018)
Neuromorphic Computing or Spiking (also called Event-Driven) Neural Systems are becoming of high interest as they potentially allow for lower power hardware computing platforms, where power consumption is data driven. ...
Ponencia
ConvNets Experiments on SpiNNaker
(IEEE Computer Society, 2015)
The SpiNNaker Hardware platform allows emulating generic neural network topologies, where each neuronto- neuron connection is defined by an independent synaptic weight. Consequently, weight storage requires an ...
Ponencia
Event-driven stereo vision with orientation filters
(IEEE Computer Society, 2014)
The recently developed Dynamic Vision Sensors (DVS) sense dynamic visual information asynchronously and code it into trains of events with sub-micro second temporal resolution. This high temporal precision makes the ...