This paper presents a sensory fusion neuromorphic dataset collected with precise temporal synchronization using a set of ...

Muscles are stretched with bursts of spikes that come from motor neurons connected to the cerebellum through the spinal ...

As localization represents the main core of various wireless sensor network applications, several localization algorithms ...

Neuromorphic computation processes sensors output in the spiking domain, which presents constraints in many cases when ...

Membrane computing is an unconventional computing paradigm that has gained much attention in recent decades because of its ...

Monitoring animals’ behavior living in wild or semi-wild environments is a very interesting subject for biologists who ...

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases ...

The use of deep learning solutions in different disciplines is increasing and their algorithms are computationally expensive ...

Prostate cancer (PCa) is one of the most commonly diagnosed cancer and one of the leading causes of death among men, with ...

El mundo ha cambiado desde la aparición del nue vo virus de la familia de los coronavirus (COVID-19), el cual fue declarado ...

Visualizing the output from event-based sensors and analyzing the information within it is crucial when developing ...

Este artículo presenta una práctica de laboratorio impartida mediante una metodología de aprendizaje basado en proyectos ...

The change from face-to-face work to teleworking caused by the pandemic has induced multiple workers to spend more time ...

El reciente Grado en Ingeniería de la Salud se originó con el planteamiento de cubrir la carencia de conoci miento sobre ...

Low-latency, low-power portable recurrent neural network (RNN) accelerators offer powerful inference capabilities for ...

This paper presents a Gated Recurrent Unit (GRU) based recurrent neural network (RNN) accelerator called Edge-DRNN designed ...

Autonomous robots have become a very popular topic within the artificial intelligence field. These systems are able to ...

In this demonstration a spiking neural network architecture for vision recognition using an FPGA spiking convolution ...

Los sistemas neuronales biológicos responden a estímulos de una forma rápida y eficiente en el movimiento motor del cuerpo, ...

Deep-learning is a cutting edge theory that is being applied to many fields. For vision applications the Convolutional Neural ...

Spiking convolutional neural networks have become a novel approach for machine vision tasks, due to the latency to process ...

Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many stateof- the-art ...

This demonstration shows a Dynamic Vision Sensor able to capture visual motion at a speed equivalent to a highspeed camera ...

In this paper we present a sub-system to convert audio information from low-power MEMS microphones with pulse density ...

The human binocular system performs very complex operations in real-time tasks thanks to neuronal specialization and several ...

Along with the proliferation of mobile devices and wireless signal coverage, IoT devices, such as smart wristbands for ...

Taking inspiration from biology to solve engineering problems using the organizing principles of biological neural computation ...

Recent biological studies have focused on understanding animal interactions and welfare. To help biolo- gists to obtain ...

Neural networks algorithms are commonly used to recognize patterns from different data sources such as audio or vision. ...

Many FPGAs vendors have recently included embedded processors in their devices, like Xilinx with ARM-Cortex A cores, ...

En este trabajo se pretende avanzar en el conocimiento y posibles implementaciones hardware de los mecanismos de Deep ...

Neuromorphic engineering takes inspiration from biology to solve engineering problems using the organizing principles of ...

Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from ...

In this demonstration we present a spiking neural network architecture for audio samples classification using SpiNNaker. ...

Although it is not a novel topic, pattern recognition has become very popular and relevant in the last years. Different ...

La sociedad avanza, y este avance favorece la aparición de nuevas necesidades, las cuales son cubiertas por profesionales ...

Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from ...

Este artículo presenta una práctica laboratorio impartida mediante una metodología de aprendizaje basado en proyectos (ABP) ...

This paper describes the software and FPGA implementation of a Retinal Ganglion Cell model which detects moving objects. ...

En el presente artículo se describe una práctica de laboratorio multitarea en el ámbito de las asignaturas de sistemas ...

The study and monitoring of the behavior of wildlife has always been a subject of great interest. Although many systems ...

Image processing is a fundamental operation in many real time applications, where lots of parallelism can be extracted. ...

Neuromorphic systems are engineering solutions that take inspiration from biological neural systems. They use spike-or ...

The study and monitoring of wildlife has always been a subject of great interest. Studying the behavior of wild animals ...

This demonstration shows how object detection and tracking are possible thanks to a new implementation which takes inspiration from the visual processing of a particular type of ganglion cell in the retina.

La enseñanza de asignaturas del ámbito de la informática está experimentando un gran cambio. La motivación del alumnado ...

Audio classification has always been an interesting subject of research inside the neuromorphic engineering field. Tools ...

The study and monitoring of wildlife has always been a subject of great interest. Studying the behavior of wildlife animals ...

Neuromorphic engineering is a growing and promising discipline nowadays. Neuro-inspiration and brain understanding applied ...

Multisensory integration is commonly used in various robotic areas to collect more environmental information using different ...

Sensors Network is an integration of multiples sensors in a system to collect information about different environment ...

Multisensory integration is commonly used in various robotic areas to collect much more information from an environment ...