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Alejandro Linares-Barranco
Researcher at University of Seville
Publications - 175
Citations - 2959
Alejandro Linares-Barranco is an academic researcher from University of Seville. The author has contributed to research in topics: Neuromorphic engineering & Field-programmable gate array. The author has an hindex of 24, co-authored 165 publications receiving 2449 citations. Previous affiliations of Alejandro Linares-Barranco include University of Zurich & ETH Zurich.
Papers
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Journal ArticleDOI
CAVIAR: A 45k Neuron, 5M Synapse, 12G Connects/s AER Hardware Sensory–Processing– Learning–Actuating System for High-Speed Visual Object Recognition and Tracking
R. Serrano-Gotarredona,M. Oster,P. Lichtsteiner,Alejandro Linares-Barranco,R. Paz-Vicente,F. Gomez-Rodriguez,Luis A. Camunas-Mesa,R Berner,M. Rivas-Perez,Tobi Delbruck,Shih-Chii Liu,Rodney J. Douglas,Philipp Hafliger,Gabriel Jimenez-Moreno,A.C. Ballcels,Teresa Serrano-Gotarredona,A.J. Acosta-Jimenez,Bernabe Linares-Barranco +17 more
TL;DR: CAVIAR is a massively parallel hardware implementation of a spike-based sensing-processing-learning-actuating system inspired by the physiology of the nervous system that achieves millisecond object recognition and tracking latencies.
Journal ArticleDOI
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Alessandro Aimar,Hesham Mostafa,Enrico Calabrese,Antonio Rios-Navarro,Ricardo Tapiador-Morales,Iulia-Alexandra Lungu,Moritz B. Milde,Federico Corradi,Alejandro Linares-Barranco,Shih-Chii Liu,Tobi Delbruck +10 more
TL;DR: In this article, the sparsity of neuron activations in CNNs is exploited to accelerate the computation and reduce memory requirements for low-power and low-latency application scenarios.
Journal ArticleDOI
An Event-Driven Multi-Kernel Convolution Processor Module for Event-Driven Vision Sensors
Luis A. Camunas-Mesa,C. Zamarreno-Ramos,Alejandro Linares-Barranco,A.J. Acosta-Jimenez,Teresa Serrano-Gotarredona,Bernabe Linares-Barranco +5 more
TL;DR: An Event-Driven Convolution Module for computing 2D convolutions on such event streams and has multi-kernel capability, which means it will select the convolution kernel depending on the origin of the event.
Journal ArticleDOI
Multicasting Mesh AER: A Scalable Assembly Approach for Reconfigurable Neuromorphic Structured AER Systems. Application to ConvNets
C. Zamarreno-Ramos,Alejandro Linares-Barranco,Teresa Serrano-Gotarredona,Bernabe Linares-Barranco +3 more
TL;DR: A modular, scalable approach to assembling hierarchically structured neuromorphic Address Event Representation (AER) systems, in which case a special bidirectional parallel-serial AER link with flow control is exploited, using the FPGA Rocket-I/O interfaces.
Journal ArticleDOI
On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing
R. Serrano-Gotarredona,Teresa Serrano-Gotarredona,A.J. Acosta-Jimenez,Clara Serrano-Gotarredona,J. A. Perez-Carrasco,Bernabe Linares-Barranco,Alejandro Linares-Barranco,Gabriel Jimenez-Moreno,A. Civit-Ballcels +8 more
TL;DR: A chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented, and discussions and results on scaling up the approach for larger pixel arrays and multilayer cortical AER systems are provided.