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of 5
pro vyhledávání: '"Jon Perez-Cerrolaza"'
Autor:
Imanol Allende, Nicholas Mc Guire, Jon Perez-Cerrolaza, Lisandro G. Monsalve, Jens Petersohn, Roman Obermaisser
Publikováno v:
IEEE Access, Vol 9, Pp 106065-106078 (2021)
Autonomous systems represent a significant leap forward in the ongoing technological evolution of dependable and safety-related systems, integrating features such as artificial intelligence, high-performance computing devices, General Purpose Operati
Externí odkaz:
https://doaj.org/article/e59221ad1c4d47fa8d33c18f60f9daa6
Autor:
Javier Fernández, Jon Perez-Cerrolaza, Irune Agirre, Alejandro J. Calderon, Jaume Abella, Francisco J. Cazorla
Publikováno v:
Applied Sciences, Vol 12, Iss 8, p 3779 (2022)
Deep learning technology has enabled the development of increasingly complex safety-related autonomous systems using high-performance computers, such as graphics processing units (GPUs), which provide the required high computing performance for the e
Externí odkaz:
https://doaj.org/article/7888046674264d12b2988c669097c25c
Publikováno v:
Computer. 56:114-117
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18d3887d15b08feccb956e485d79b601
https://doi.org/10.1109/mc.2023.3235093
https://doi.org/10.1109/mc.2023.3235093
Autor:
Jon Perez-Cerrolaza, Jaume Abella, Leonidas Kosmidis, Alejandro J. Calderon, Francisco Cazorla, Jose Luis Flores
Publikováno v:
ACM Computing Surveys
Graphics Processing Unit (GPU) devices and their associated software programming languages and frameworks can deliver the computing performance required to facilitate the development of next-generation high-performance safety-critical systems such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60362dce8ac17b675e3d3a6852ecf40d
https://hdl.handle.net/2117/386460
https://hdl.handle.net/2117/386460
Autor:
Axel Brando, Isabel Serra, Enrico Mezzetti, Francisco J. Cazorla, Jon Perez-Cerrolaza, Jaume Abella
An increasing number of critical functionalities integrated in embedded critical systems rely on deep learning (DL) technology. This article summarizes certain key aspects of DL’s intrinsic stochastic and training-data-dependent nature that are at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::143b86d2ab963031f7d977ed438a4d0b
https://hdl.handle.net/2117/387765
https://hdl.handle.net/2117/387765