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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 ...
Capítulo de Libro
Study of Communication Issues in Dynamically Scalable Cloud-Based Vision Systems for Mobile Robots
(Springer, 2016)
Thanks to the advent of technologies like Cloud Computing, the idea of computation offloading of robotic tasks is more than feasible. Therefore, it is possible to use legacy embedded systems for computationally heavy ...
Artículo
Analysis of Android Device-Based Solutions for Fall Detection
(MDPI, 2015)
Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the ...
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 ...
Artículo
Approaching Retinal Ganglion Cell Modeling and FPGA Implementation for Robotics
(MDPI, 2018)
Taking inspiration from biology to solve engineering problems using the organizing principles of biological neural computation is the aim of the field of neuromorphic engineering. This field has demonstrated success in ...
Artículo
An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems
(IEEE Computer Society, 2022)
Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are ...
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 ...
Artículo
Parallel connected-Component-Labeling based on homotopy trees
(Elsevier, 2020)
Taking advantage of the topological and isotopic properties of binary digital images, we present here anew algorithm for connected component labeling (CLL). A local-to-global treatment of the topologicalinformation within ...
Ponencia
Práctica de desarrollo de interfaces hardware/software para la monitorización del estado de un PC
(AENUI: Asociación de Enseñantes Universitarios de Informática, 2016)
Este artículo presenta una práctica laboratorio impartida mediante una metodología de aprendizaje basado en proyectos (ABP) [1] para dotar de la capacidad de diseñar y desarrollar un monitor del estado de un ordenador, ...
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 ...