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Mostrando ítems 1-10 de 13
Ponencia
Fast Pipeline 128x128 Pixel Spiking Convolution Core for Event-Driven Vision Processing in FPGAs
(IEEE. Institute of Electrical and Electronics Engineers, 2015)
This paper describes a digital implementation of a parallel and pipelined spiking convolutional neural network (SConvNet) core for processing spikes in an event-driven system. Event-driven vision systems use typically ...
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
Live Demonstration: Multiplexing AER Asynchronous Channels over LVDS Links with Flow-Control and Clock- Correction for Scalable Neuromorphic Systems
(IEEE Computer Society, 2017)
In this live demonstration we exploit the use of a serial link for fast asynchronous communication in massively parallel processing platforms connected to a DVS for realtime implementation of bio-inspired vision processing ...
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 ...
Artículo
Active Perception with Dynamic Vision Sensors. Minimum Saccades with Optimum Recognition
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Vision processing with Dynamic Vision Sensors (DVS) is becoming increasingly popular. This type of bio-inspired vision sensor does not record static scenes. DVS pixel activity relies on changes in light intensity. In ...
Tesis Doctoral
Diseño digital para sistemas bio-inspirados neuromórficos de proceso de visión.
(2018-04-04)
Artificial Intelligence (AI) is an exciting technology that flourished in this century. One of the goals for this technology is to give learning ability to computers. Currently, machine intelligence surpasses human ...
Ponencia
Hardware Implementation of Convolutional STDP for On-line Visual Feature Learning
(IEEE. Institute of Electrical and Electronics Engineers, 2017)
We present a highly hardware friendly STDP (Spike Timing Dependent Plasticity) learning rule for training Spiking Convolutional Cores in Unsupervised mode and training Fully Connected Classifiers in Supervised ...
Ponencia
Multiplexing AER Asynchronous Channels over LVDS Links with Flow-Control and Clock-Correction for Scalable Neuromorphic Systems
(IEEE Computer Society, 2017)
Address-Event-Representation (AER) is a widely extended asynchronous technique for interchanging “neural spikes” among different hardware elements in Neuromorphic Systems. Conventional AER links use parallel physical ...
Ponencia
Live demonstration: Hardware implementation of convolutional STDP for on-line visual feature learning
(IEEE. Institute of Electrical and Electronics Engineers, 2017)
We present live demonstration of a hardware that can learn visual features on-line and in real-time during presentation of objects. Input Spikes are coming from a bio-inspired silicon retina or Dynamic Vision Sensor (DVS) ...
Ponencia
Hybrid Neural Network, An Efficient Low-Power Digital Hardware Implementation of Event-based Artificial Neural Network
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Interest in event-based vision sensors has proliferated in recent years, with innovative technology becoming more accessible to new researchers and highlighting such sensors’ potential to enable low-latency sensing at ...