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Mostrando ítems 1-10 de 23
Ponencia
On scalable spiking convnet hardware for cortex-like visual sensory processing systems
(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 ...
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
Voltage Mode Driver for Low Power Transmission of High Speed Serial AER Links
(IEEE Computer Society, 2011)
This paper presents a voltage-mode high speed driver to transmit serial AER data in scalable multi-chip AER systems. To take advantage of the asynchronous nature of AER (Address Event Representation) streams, this ...
Artículo
Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform
(Elsevier, 2020)
Neural networks have enabled great advances in recent times due mainly to improved parallel computing capabilities in accordance to Moore’s Law, which allowed reducing the time needed for the parameter learning of complex, ...
Ponencia
A Current Attenuator for Efficient Memristive Crossbars Read-Out
(IEEE Computer Society, 2019)
This paper presents a new current attenuator circuit to scale down the inference currents in memristor based crossbars that drive integrate-and-fire neurons, which subsequently allows to reduce the size of integrating ...
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 ...