Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Evelina Forno"'
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Spiking Neural Networks (SNNs), known for their potential to enable low energy consumption and computational cost, can bring significant advantages to the realm of embedded machine learning for edge applications. However, input coming from standard d
Externí odkaz:
https://doaj.org/article/1886ca102fb144a794d78bc9b72ae584
Braille letter reading: A benchmark for spatio-temporal pattern recognition on neuromorphic hardware
Autor:
Simon F. Müller-Cleve, Vittorio Fra, Lyes Khacef, Alejandro Pequeño-Zurro, Daniel Klepatsch, Evelina Forno, Diego G. Ivanovich, Shavika Rastogi, Gianvito Urgese, Friedemann Zenke, Chiara Bartolozzi
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for numerous real-world activities. Recent deep learning approaches have reached outstanding accuracies in such tasks, but their implementation on conventiona
Externí odkaz:
https://doaj.org/article/963e9e0870964aecaa8aa10aaefba422
Publikováno v:
Journal of Low Power Electronics and Applications, Vol 11, Iss 2, p 25 (2021)
SpiNNaker is a neuromorphic hardware platform, especially designed for the simulation of Spiking Neural Networks (SNNs). To this end, the platform features massively parallel computation and an efficient communication infrastructure based on the tran
Externí odkaz:
https://doaj.org/article/8b60e39802884841b874a0953cbb5d4e
Braille letter reading: A benchmark for spatio-temporal pattern recognition on neuromorphic hardware
Autor:
Simon F, Müller-Cleve, Vittorio, Fra, Lyes, Khacef, Alejandro, Pequeño-Zurro, Daniel, Klepatsch, Evelina, Forno, Diego G, Ivanovich, Shavika, Rastogi, Gianvito, Urgese, Friedemann, Zenke, Chiara, Bartolozzi
Publikováno v:
Frontiers in Neuroscience, 16:951164. Frontiers Media SA
Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for numerous real-world activities. Recent deep learning approaches have reached outstanding accuracies in such tasks, but their implementation on conventiona
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0435552f5cfd6a499c2737db73733f6e
https://research.rug.nl/en/publications/4fdb1f45-d7d0-462c-aeed-9fb89c74c413
https://research.rug.nl/en/publications/4fdb1f45-d7d0-462c-aeed-9fb89c74c413
Publikováno v:
Journal of Low Power Electronics and Applications, Vol 11, Iss 25, p 25 (2021)
Journal of Low Power Electronics and Applications
Volume 11
Issue 2
Journal of Low Power Electronics and Applications
Volume 11
Issue 2
SpiNNaker is a neuromorphic hardware platform, especially designed for the simulation of Spiking Neural Networks (SNNs). To this end, the platform features massively parallel computation and an efficient communication infrastructure based on the tran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::827b8a741d0ab6fed2e508c17e631dc0
https://www.mdpi.com/2079-9268/11/2/25
https://www.mdpi.com/2079-9268/11/2/25
Nowadays, localization features are widespread in low-cost and low-power IoT applications such as bike-sharing, off-road vehicle fleet management, and theft prevention of smart devices. For such use cases, since the item to be tracked is inexpensive,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb15fac9517a04f6db6248b1cb21921f
http://hdl.handle.net/11583/2846916
http://hdl.handle.net/11583/2846916
Autor:
Vittorio Fra, Evelina Forno, Riccardo Pignari, Terrence C Stewart, Enrico Macii, Gianvito Urgese
Publikováno v:
Neuromorphic Computing and Engineering. 2:014006
Human activity recognition (HAR) is a classification problem involving time-dependent signals produced by body monitoring, and its application domain covers all the aspects of human life, from healthcare to sport, from safety to smart environments. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06858737bc895d4dc1086cf5fc773b89
https://doi.org/10.1088/2634-4386/ac4c38
https://doi.org/10.1088/2634-4386/ac4c38
Publikováno v:
VLSI-SoC
Quantum Annealing (QA) is an emerging technique, derived from Simulated Annealing, providing metaheuristics for multivariable optimisation problems. Studies have shown that it can be applied to solve NP-hard problems with faster convergence and bette
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4bc3e5600d9c701a1c49fdeb7fc974ab
http://hdl.handle.net/11583/2725886
http://hdl.handle.net/11583/2725886
Autor:
Gianvito Urgese, Evelina Forno, Enrico Macii, Francesco Barchi, Emanuele Parisi, Andrea Acquaviva
Publikováno v:
Electronics
Volume 8
Issue 11
Volume 8
Issue 11
SpiNNaker is a neuromorphic globally asynchronous locally synchronous (GALS) multi-core architecture designed for simulating a spiking neural network (SNN) in real-time. Several studies have shown that neuromorphic platforms allow flexible and effici
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::468841d6ab045b7ba5be6785002777fa
https://doi.org/10.3390/electronics8111342
https://doi.org/10.3390/electronics8111342