Alejandro Linares-Barranco
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View article: Deep Learning-Based Assessment of Brainstem Volume Changes in Spinocerebellar Ataxia Type 2 (SCA2): A Study on Patients and Preclinical Subjects
Deep Learning-Based Assessment of Brainstem Volume Changes in Spinocerebellar Ataxia Type 2 (SCA2): A Study on Patients and Preclinical Subjects Open
Spinocerebellar ataxia type 2 (SCA2) is a neurodegenerative disorder marked by progressive brainstem and cerebellar atrophy, leading to gait ataxia. Quantifying this atrophy in magnetic resonance imaging (MRI) is critical for tracking dise…
View article: Deep Learning-Based Assessment of Brainstem Volume Changes in Spinocerebellar Ataxia Type 2 (SCA2): A Study on Patients and Preclinical Subjects
Deep Learning-Based Assessment of Brainstem Volume Changes in Spinocerebellar Ataxia Type 2 (SCA2): A Study on Patients and Preclinical Subjects Open
Spinocerebellar ataxia type 2 (SCA2) is a neurodegenerative disorder marked by progressive brainstem and cerebellar atrophy, leading to gait ataxia. Quantifying this atrophy in magnetic resonance imaging (MRI) is critical for tracking dise…
View article: Deep Learning-Based Assessment of Brainstem Volume Changes in Spinocerebellar Ataxia Type 2 (SCA2): A Study on Patients and Preclinical Subjects
Deep Learning-Based Assessment of Brainstem Volume Changes in Spinocerebellar Ataxia Type 2 (SCA2): A Study on Patients and Preclinical Subjects Open
Spinocerebellar ataxia type 2 (SCA2) is a neurodegenerative disorder marked by progressive brainstem and cerebellar atrophy, leading to gait ataxia. Quantifying this atrophy in magnetic resonance imaging (MRI) is critical for tracking dise…
View article: Rapid learning with phase-change memory-based in-memory computing through learning-to-learn
Rapid learning with phase-change memory-based in-memory computing through learning-to-learn Open
There is a growing demand for low-power, autonomously learning artificial intelligence (AI) systems that can be applied at the edge and rapidly adapt to the specific situation at deployment site. However, current AI models struggle in such…
View article: Towards spiking analog hardware implementation of a trajectory interpolation mechanism for smooth closed-loop control of a spiking robot arm
Towards spiking analog hardware implementation of a trajectory interpolation mechanism for smooth closed-loop control of a spiking robot arm Open
Neuromorphic engineering aims to incorporate the computational principles found in animal brains, into modern technological systems. Following this approach, in this work we propose a closed-loop neuromorphic control system for an event-ba…
View article: Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator
Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator Open
With the rise of artificial intelligence, neural network simulations of biological neuron models are being explored to reduce the footprint of learning and inference in resource-constrained task scenarios. A mainstream type of such network…
View article: A systematic comparison of deep learning methods for Gleason grading and scoring
A systematic comparison of deep learning methods for Gleason grading and scoring Open
Prostate cancer is the second most frequent cancer in men worldwide after lung cancer. Its diagnosis is based on the identification of the Gleason score that evaluates the abnormality of cells in glands through the analysis of the differen…
View article: Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing
Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing Open
There is a growing demand for low-power, autonomously learning artificial intelligence (AI) systems that can be applied at the edge and rapidly adapt to the specific situation at deployment site. However, current AI models struggle in such…
View article: Towards neuromorphic FPGA-based infrastructures for a robotic arm
Towards neuromorphic FPGA-based infrastructures for a robotic arm Open
Muscles are stretched with bursts of spikes that come from motor neurons connected to the cerebellum through the spinal cord. Then, alpha motor neurons directly innervate the muscles to complete the motor command coming from upper biologic…
View article: Closed-loop sound source localization in neuromorphic systems
Closed-loop sound source localization in neuromorphic systems Open
Sound source localization (SSL) is used in various applications such as industrial noise-control, speech detection in mobile phones, speech enhancement in hearing aids and many more. Newest video conferencing setups use SSL. The position o…
View article: LIPSFUS: A neuromorphic dataset for audio-visual sensory fusion of lip reading
LIPSFUS: A neuromorphic dataset for audio-visual sensory fusion of lip reading Open
This paper presents a sensory fusion neuromorphic dataset collected with precise temporal synchronization using a set of Address-Event-Representation sensors and tools. The target application is the lip reading of several keywords for diff…
View article: Editorial: Powering the next-generation IoT applications: new tools and emerging technologies for the development of Neuromorphic System of Systems
Editorial: Powering the next-generation IoT applications: new tools and emerging technologies for the development of Neuromorphic System of Systems Open
EDITORIAL article Front. Neurosci., 04 May 2023Sec. Neuromorphic Engineering Volume 17 - 2023 | https://doi.org/10.3389/fnins.2023.1197918
View article: A comparative study of the inter-observer variability on Gleason grading against Deep Learning-based approaches for prostate cancer
A comparative study of the inter-observer variability on Gleason grading against Deep Learning-based approaches for prostate cancer Open
The obtained results show that deep learning-based automatic diagnosis systems could help reduce the widely-known inter-observer variability that is present among pathologists and support them in their decision, serving as a second opinion…
View article: LIPSFUS: A neuromorphic dataset for audio-visual sensory fusion of lip reading
LIPSFUS: A neuromorphic dataset for audio-visual sensory fusion of lip reading Open
This paper presents a sensory fusion neuromorphic dataset collected with precise temporal synchronization using a set of Address-Event-Representation sensors and tools. The target application is the lip reading of several keywords for diff…
View article: Event-Based Sound Source Localization in Neuromorphic Systems
Event-Based Sound Source Localization in Neuromorphic Systems Open
Sound source localization is used in various applications such as industrial noise-control, speech detection in mobile phones, speech enhancement in hearing aids and many more. Newest video conferencing setups use sound source localization…
View article: Event-Based Sound Source Localization in Neuromorphic Systems
Event-Based Sound Source Localization in Neuromorphic Systems Open
Sound source localization is used in various applications such as industrial noise-control, speech detection in mobile phones, speech enhancement in hearing aids and many more. Newest video conferencing setups use sound source localization…
View article: An MPSoC-based on-line Edge Infrastructure for Embedded Neuromorphic Robotic Controllers
An MPSoC-based on-line Edge Infrastructure for Embedded Neuromorphic Robotic Controllers Open
In this work, an all-in-one neuromorphic controller system with reduced latency and power consumption for a robotic arm is presented. Biological muscle movement consists of stretching and shrinking fibres via spike-commanded signals that c…
View article: Convolutional Neural Networks for Segmenting Cerebellar Fissures from Magnetic Resonance Imaging
Convolutional Neural Networks for Segmenting Cerebellar Fissures from Magnetic Resonance Imaging Open
The human cerebellum plays an important role in coordination tasks. Diseases such as spinocerebellar ataxias tend to cause severe damage to the cerebellum, leading patients to a progressive loss of motor coordination. The detection of such…
View article: An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems
An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems Open
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 the key ingredien…
View article: A Deep-Learning Based Posture Detection System for Preventing Telework-Related Musculoskeletal Disorders
A Deep-Learning Based Posture Detection System for Preventing Telework-Related Musculoskeletal Disorders Open
The change from face-to-face work to teleworking caused by the pandemic has induced multiple workers to spend more time than usual in front of a computer; in addition, the sudden installation of workstations in homes means that not all of …
View article: Wildlife Monitoring on the Edge: A Performance Evaluation of Embedded Neural Networks on Microcontrollers for Animal Behavior Classification
Wildlife Monitoring on the Edge: A Performance Evaluation of Embedded Neural Networks on Microcontrollers for Animal Behavior Classification Open
Monitoring animals’ behavior living in wild or semi-wild environments is a very interesting subject for biologists who work with them. The difficulty and cost of implanting electronic devices in this kind of animals suggest that these devi…
View article: Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed
Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed Open
Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018. As it has been estimated, its mortality will double by 2040, mostly in countries with l…
View article: ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers
ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers Open
Compared to classic robotics, biological nervous systems respond to stimuli in a fast and efficient way regarding the body motor actions. Decision making, once the sensory information arrives to the brain, is in the order of ms, while the …
View article: An Event-Based, Digital Time Difference Encoder Model Implementation for Neuromorphic Systems
An Event-Based, Digital Time Difference Encoder Model Implementation for Neuromorphic Systems Open
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 the key ingredien…
View article: An Event-Based, Digital Time Difference Encoder Model Implementation for Neuromorphic Systems
An Event-Based, Digital Time Difference Encoder Model Implementation for Neuromorphic Systems Open
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 the key ingredien…
View article: An Event-Based, Digital Time Difference Encoder Model Implementation for Neuromorphic Systems
An Event-Based, Digital Time Difference Encoder Model Implementation for Neuromorphic Systems Open
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 the key ingredien…
View article: Live Demonstration: Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance
Live Demonstration: Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance Open
The brain is able to solve complex tasks in real time by combining different sensory cues with previously acquired knowledge. Inspired by the brain, we designed a neuromorphic demonstrator which combines auditory and visual input to find a…