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Mostrando ítems 1-10 de 14
Ponencia
Work-in-Progress: A Neuromorphic Approach of the Sound Source Localization Task in Real-Time Embedded Systems
(ACM Digital Library, 2019)
Autonomous robots have become a very popular topic within the artificial intelligence field. These systems are able to perform difficult or risky tasks that could be dangerous when done by humans or trained animals. ...
Ponencia
Live Demonstration: Neuromorphic Row-by-Row Multi-convolution FPGA Processor-SpiNNaker architecture for Dynamic-Vision Feature Extraction
(IEEE Computer Society, 2019)
In this demonstration a spiking neural network architecture for vision recognition using an FPGA spiking convolution processor, based on leaky integrate and fire neurons (LIF) and a SpiNNaker board is presented. The ...
Artículo
Embedded neural network for real-time animal behavior classification
(Elsevier, 2018)
Recent biological studies have focused on understanding animal interactions and welfare. To help biolo- gists to obtain animals’ behavior information, resources like wireless sensor networks are needed. More- over, large ...
Ponencia
Live demonstration — Multilayer spiking neural network for audio samples classification using SpiNNaker
(IEEE Computer Society, 2017)
In this demonstration we present a spiking neural network architecture for audio samples classification using SpiNNaker. The network consists of different leaky integrate-and-fire neuron layers. The connections between ...
Ponencia
Event-based Row-by-Row Multi-convolution engine for Dynamic-Vision Feature Extraction on FPGA
(IEEE Computer Society, 2018)
Neural networks algorithms are commonly used to recognize patterns from different data sources such as audio or vision. In image recognition, Convolutional Neural Networks are one of the most effective techniques due ...
Ponencia
Spiking row-by-row FPGA Multi-kernel and Multi-layer Convolution Processor.
(IEEE Computer Society, 2019)
Spiking convolutional neural networks have become a novel approach for machine vision tasks, due to the latency to process an input stimulus from a scene, and the low power consumption of these kind of solutions. ...
Ponencia
A Sensor Fusion Horse Gait Classification by a Spiking Neural Network on SpiNNaker
(Springer, 2016)
The study and monitoring of the behavior of wildlife has always been a subject of great interest. Although many systems can track animal positions using GPS systems, the behavior classification is not a common task. For ...
Ponencia
A 20Mevps/32Mev event-based USB framework for neuromorphic systems debugging
(IEEE Computer Society, 2016)
Neuromorphic systems are engineering solutions that take inspiration from biological neural systems. They use spike-or event-based representation and codification of the information. This codification allows performing ...
Ponencia
System based on inertial sensors for behavioral monitoring of wildlife
(IEEE Computer Society, 2015)
Sensors Network is an integration of multiples sensors in a system to collect information about different environment variables. Monitoring systems allow us to determine the current state, to know its behavior and sometimes ...
Ponencia
Accuracy Improvement of Neural Networks Through Self-Organizing-Maps over Training Datasets
(Springer, 2017)
Although it is not a novel topic, pattern recognition has become very popular and relevant in the last years. Different classification systems like neural networks, support vector machines or even complex statistical ...