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Mostrando ítems 1-10 de 13
Artículo
Real-time detection of uncalibrated sensors using neural networks
(Springer, 2022)
Nowadays, sensors play a major role in several fields, such as science, industry and everyday technology. Therefore, the information received from the sensors must be reliable. If the sensors present any anomalies, serious ...
Artículo
AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks
(MDPI, 2021)
Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits ...
Artículo
A study on the use of Edge TPUs for eye fundus image segmentation
(Elsevier, 2021)
Medical image segmentation can be implemented using Deep Learning methods with fast and efficient segmentation networks. Single-board computers (SBCs) are difficult to use to train deep networks due to their memory and ...
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, ...
Artículo
Neuromorphic adaptive spiking CPG towards bio-inspired locomotion
(Elsevier, 2022)
In recent years, locomotion mechanisms exhibited by vertebrate animals have been the inspiration for the improvement in the performance of robotic systems. These mechanisms include the adaptability of their locomotion ...
Artículo
Interfacing PDM MEMS Microphones with PFM Spiking Systems: Application for Neuromorphic Auditory Sensors
(Springer, 2022)
Neuromorphic computation processes sensors output in the spiking domain, which presents constraints in many cases when converting information to spikes, loosing, as example, temporal accuracy. This paper presents a spike-based ...
Artículo
Preventive Conservation and Restoration Monitoring of Heritage Buildings Based on Fuzzy Logic
(Taylor and Francis, 2022)
This article discusses the usability of the Art-Risk 3.0 software for research on the conservation of heritage buildings. It is a new and free software based on fuzzy logic, which enables the assessment of preventive ...
Ponencia
Event-Driven Configurable Module with Refractory Mechanism for ConvNets on FPGA
(IEEE Computer Society, 2018)
We have developed a fully configurable event-driven convolutional module with refractory period mechanism that can be used to implement arbitrary Convolutional Neural Networks (ConvNets) on FPGAs following a 2D array ...
Artículo
Real-time detection of uncalibrated sensors using Neural Networks
(Cornell University, 2021)
Nowadays, sensors play a major role in several contexts like science, industry and daily life which benefit of their use. However, the retrieved information must be reliable. Anomalies in the behavior of sensors can give ...
Artículo
ART-RISK 3.0 a fuzzy—based platform that combine GIS and expert assessments for conservation strategies in cultural heritage
(Elsevier, 2022)
eritage preservation poses numerous difficulties, especially in emergency situations or during bud get cuts. In these contexts, having tools that facilitate efficient and rapid management of hazards vulnerabilities is a ...